In this paper we propose the new adaptive control algorithm by using S-G algorithm based on the error equations derived by Slotine. We verify the validity of the proposed controller and convergence of three type parameter estimation law based on S-G algorithm from the computer simulation.

This paper presents deterministic and adaptive control laws for two-link flexible arm. The flexible arm has considerable structural flexibility. Because of its flexbility, dynamic equations are very complex and difficult to get, dynamic equations for two-link flexible arm are derived from Bernoulli-Euler beam theory and Lagrangian equation. Using the fact that matrix is skew symmetric, controllers which have a simplified structure with less computational burden are proposed by using Lyapunov stability theory.

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

The control of the motion of a mobile robot is studied. The driving and steering motor assembly is located in the front of the mobile robot. The position of the mobile robot is determined by the steering angle and driving distance. For the controller design, a time-series multivariate model of the autogressive exogenous (ARX) type is used to describe the input-output relation. The discounted least square method is used to estimate parameters of the time-series model. A self-tuning controller is so designed that the position of the center of the mobile robot track the given trajectory. Simulation result controlled by a self-tuning controller is presented to illustrate the approach.

DD motor, with large rotor inertia & wide range of torque, is different from other servo motor in control & drive characteristic. In this paper, for the development of flexible DD robot, we introduced the h/w & s/w technics of DSP to construct the velocity, position & torque control strategies and integrated 2 axes special purpose DD servo dirver into one VME bus.

This paper suggests Kalman filter formulation using by precision GINS output angle for SDINS initial transfer alignment of missile. The Kalman filter model was derived from quaternion parameters and the transfer alignment system by angle matching method satisfies azimuth observability in horizontal angular motion. The estimated error of SDINS attitude settles to less 3mrad(1.sigma.) in 200 seconds at proper sea state.

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.

In this paper, we design a multirate controller for a given multirate sampled-data system which has a periodic output measurement scheme. A sufficient condition for maintaining observability in multirate sampled-data systems is given first. The design strategy for disturbance rejection is proposed. The proposed controller has IMC structure, and can be deomposed into a disturbance estimator and the inverse of fast plants.

A method of finding the optimal actuator location for efficient control of the modes of interest is presented. The proposed approach relies on certain quantitive measure of degree of controllability based on the controllability grammian. This measure proves to be useful for regulating problem of the undamped system and can be extended to cover the tracking problem of the viscous damped system. The example of the uniform cantilever beam is given to verify the effectiveness of the method.

Conventional active control algorithm for duct system is developed without considering problems of constrained structure. Therefore it destroys the constrained structures of the weights or parameters. A new LMS algorithm, which does keep the constraints, is proposed for systems with known constrained structure. It is based on error-back propagation. The stability analysis and simulation example are also included.

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters, time delay, and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursive form by using new functions of two dimensional autocorrelations and cross-correlations of inputs and outputs. The proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

In this paper we present the performance bounds of the optimal FIR filter in continuous time systems with modeling uncertainty. The performance measure bounds are calculated from the estimation error covariance bounds of the optimal FIR filter and the suboptimal FIR filter. Performance error bounds range are expressed by the upper bounds on the estimation error covariance difference between the real and nominal values in case of the systems with noise uncertainty or model uncertainty. The performance bounds of the systems are derived on the assumption that the system uncertainty and the estimation error covariance are imperfectly known a priori. The estimation error bounds of the optimal FIR filter is compared with those of the Kalman filter via a numerical example applied to the estimation of the motion of an aircraft carrier at sea, which shows the former has better performances than the latter.

The performance of the BEWE(Bearing Estimation Without Eigendecomposition) algorithm depends on the sensor outputs which are selected to construct the projection matrix. In this paper, we construct the covariance matrix of the bearing estimates for two targets and propose the criterion to select the sensor outputs which minimize the covariance matrix. The computer simulation conforms that the estimation error is smallest when the sensor outputs are selected based on the proposed criterion.

This paper presents an Auto-Drive-Guidance System which provides a path to the destination with the shortest driving distance(or time), as well as service information such as the location of gas stations, hospitals, or police stations. This system displays on the monitor screen the best driving path to the destination, points the current car position on the map, informs the driver of current position by voice whenever the car passes well-known places, or displays the map the driver wishes to view. With this system, driving becomes more comfortable, and traffic jams will be greatly reduced. As a result, gasoline consumption will be reduced and so air pollution. The system can also be applied to such areas as communication network, geographic map, and tour information.

A supervisory controller design technique for multiple-AGV systems is presented in this paper. The guidepath is represented in the form of a network, and its modifications are easily tested. The network has two-layered structure, where the path sets between each two nodes are made in advance using the K-shortest path algorithm. Occupation times for all links are stored in link-occupation table, and are updated after the dispatching time. Dispatching and scheduling for each AGV are optimized in terms of minimum-time objectives. In all times, the paths are guaranteed to be conflict-free and deadlock-free. The simplicity and flexibility on this control scheme make the supervisory suitable for real applications.

This paper introduces an ARV(Autonomous Road Vehicle) system which can run on orads without help of a driver by detecting road boundaries through computer vision. This vehicle can also detect obstacles in front through sonar sensors and infrared sensors. This system largely consists of a handle steering module and a braking module. From road boundaries, the steering module determines handle turn angle. The braking module stops or decelerates to avoid collision depending on the relative speeds and distance to the obstacles detected by different sensors. This ARV system has been implemented in a small jeep and can run 30-40 km/h city traffic. In this paper, we illustrate the structure of the ARV systems and its operation principle.

In this paper, the method for navigation and obstacle avoidance of an autonomous mobile robot is proposed. It is based on the fuzzy inference system which enables to deal with imprecise and uncertain information, and on the neural network which enables to learn input and output pattern data obtained from ultrasonic sensors. For autonomous navigation, the wall-following navigation utilizing input and output data by an expert's control action is constructed. An approach by the neural network is developed for the obstacle avoidance because of the redundant input data. For an autonomous navigation, the fuzzy control and the control of the neural network are integrated and its feasibility is demonstrated by means of experiment.

This paper discusses an approach to real-time path-planning of mobile robot navigating amidst multiple obstacles. Given an environment with the coordinates of known obstacles, the moving area of a mobile robot is divided into many patches of triangles with small edge length, in order to ensure a path better than those reported in the literature. After finding a minimum-distance to minimize the number of turns and total path-length by two-step path-revision and path-smmothing.

A new model for the construction of a sonar map in a specular environment has been developed ad implemented. In a real world where most of the object surfaces are specular ones, a sonar sensor suffers from a multipath effect which results in a wrong interpretation of an objects's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

This paper represents mechanical compliance & ZMP(Zero Moment Point) control algorithm for IWR(Inha Walking Robot) system. In case of walking in different environments, a biped walking robot must vary its gait(walking period or step length, etc.) according to the environments. However, most of biped walking robots do not have the capability to change their gaits or need more complex control algorithm, because ZMP cannot be defined in their control algorithm. Therefore new linear type with balancing joint is proposed which is used as an aid in balancing & ZMP control itself. In IWR system, ZMP can be defined by solving differential equations and it does not need to be predefined ZMP trajectory. Furthermore we can input the desired ZMP position. In parallel with the development, we also considered a mechanical compliance for reducing the inverse kinematics, dynamics and the control complexity. It will figure out some powerful adaptation with 3D irregular terrains.

This paper describes a method of producing maps of an indoor environment with an autonomous mobile robot equipped with sonar array. This method uses the certainty grid suitable for accommodation of inaccurate sensor data and real-time navigation. Each grid contains a certainty vale that indicates the measure of confidence that an obstacle exists within th grid area. The scheduled firing method is used to eliminate the crosstalk between ultrasonic sensors. The effectiveness of the method is verified by a series of experiments.

When a mobile robot moves around autonomously without man-made landmarks, it is essential to recognize the placement of surrounding objects especially for current position estimation, obstacle avoidance, or homing into the work station. In this paper, we propose a novel approach to recognize the floor paln for indoor mobile robot navigation using ultrasonic time-of-flight method. We model the floor plan as a collection of polygonal plane objects and recognize the floor plan by locating edges and vertices of the objects. The direction is estimated by the patterns of transmission beam and reception sensitivity of the ultrasonic transducer, and the distance is estimated by the correlation detection method. We show the validity of the proposed approach through experimental results and discuss the resolution and the accuracy of the estimation of direction and distance.

This paper presents neural network based position estimation method in slippery environment as an approach to solve one of problems which are engaged in dead reckoning method. Position estimator is composed of slip detector and linear velocity estimator. Both of them are based on the fact that dynamic characteristic of mobile robot in slippery environment is different from the case without slip. To find out the dynamic relation among driving torque, angular acceleration of driving wheel and linear acceleration of mobile robot, accelerometer is used for measuring acceleration of mobile robot and neural network is used for dynamic system identifier in slippery environment.

In this paper, a robust reduced order adaptive controller is proposed based on Internal Model Control(IMC) structure for stochastic linear stable systems. The concept of gain margin is utilized to make the adaptive IMC controller robust. We prove the stability of the proposed adaptive IMC system for stable plants under the assumption that upper bounds for system orders are known. Simulation results show that the proposed method has good performance and stability robustness.

This paper considers the adaptive predictive control problem of a system characterized by a multiplexed measurements and multirate sampling mechanism. Plant outputs are measured in various sampling rates through a multiplexed measurement system where a single common instrument is shared by several controllers. In general, output measurement sampling rate is assumed to be slower that input update rate. An adaptive predictive control algorithm is developed for systems with multiplexed measurements.

The neural network MRAC system is presented. The purpose of this paper is applied to a plant that is to be controlled in a strongly nonlinear environment. The proposed system has a learning and adaptive ability in the varying environment by using the back-propagation learning algorithm based on Lyapunov stability theory. N.N. regulator is a part of overall system and is guaranteed to be stable in initial stage. Nonlinear terms of the varying mass, colilori, centifugal, and gravity are compensated for by feedforward N.N. regulator. And the feedback controller (adaptive mechanism) works to eliminate errors of position, velocity which the feedforward controller cannot compensate for. Finally, the proposed system will be demonstrated by simulation of a two d.o.f robot manipulator.

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an inproved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing force coming from the difference between th actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

This paper presents robustness properties of the Kalman Filter ad the associated LQG/LTR method for linear time-invariant systems having delays in both the state and output. A circle condition relating to the return difference matrix associated with the Kalman filter is derived. Using this circle condition, it is shown that the Kalman filter guarantees(1/2, .inf.) gain margin and .+-.60.deg. phase margin, which are the same as those for nondelay systems. However, it is shown that, even for minimum phase plants, the LQG/LTR method can not recover the target loop transfer function. Instead, an upper bound on the recovery error is obtained using an upper bound of the solution of the Kalman filter Riccati equations. Finally, some dual properties between output-delated system and input-delayed systems are exploited.

As the worst-case analysis for interval plants, a conjecture whether the supremum of the integral of square error(ISE) is attained at the extreme point such as vertices, Kharitonov vertices, CB segment, and edges is suggested. We present a sufficient condition for which the worst performance index occurs at one ofvertices of uncertain parameter space. Numerical examples are also given.

In this paper, we present an algorithmic technique for determining a feedback compensator which will stabilize the interval dynamic system, specifically, the robust regulator design for interval plants. The approach taken here is to allow the system parameters to live within prescribed intervals then design a dynamic feedback compensator which guarantees closed-loop system stable. The main contribution of this paper is the idea of introducing a "simplified Kharitonov's result" for low order polynomials to search for suitable compensator parameters in the compensator parameter space to make the uncertain syste robust. We also design the robust regulator which will D-stabilize (have the closed-loop poles in the left sector only) the dynamic interval system while having good performance. The nuerical examples are given to show the substantially improved robustness which results from our approach. approach.

In general, for underwater vehicles in low speed, depthkeeping operations are carried out by using the variation of the weight in the seaway tank. The depthkeeping control of underwater vehicles is difficult because of the deadzone effect in the flow rate control valve. In this paper, the nonlinear multivariable QLQG/LTR control system using a seaway tank and bow planes is synthesized in order to improve the performance of the depth control system. The computer simulation results show the multivariable QLQG/LTR control system has good depth control performance under the deadzone effect.

The goal of this paper is to develop an on-board controller for a model helicopter's hovering attitude control, using i8096 one-chip microcontroller. Required controller algorithm is programmed in ASM-96 assembly language and downloaded into an i8096 microcontroller. The performance of hovering flight using this system is verified by experiments with the model helicopter mounted on an instrumented flight stand where 3 potentiometers and an optical proximity sensor measure te attitude and main rotor speed of the helicopter.

This paper presents an ARW(Anti-Reset Windup) method for discrete-time control systems with saturation nonlinearites. The method is motivated by the concept of the equilibrium point. The design parameters of the ARW scheme is explicitly derived by minimizing a reasonable performance index. The proposed method is closely related with the singular perturbed theory. The proposed method is applicable to any open-loop stable plants with saturation nonlinearities whose controllers are determined a priori by some design technique.

A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type 1), linear inference (type 2), and modified linear inference (type 3). The fuzzy c-means clustering and modified complex methods are used in order to identify the preise structure and parameter of fuzzy implication rules, respectively and the least square method is utilized for the identification of optimal consequence parameters. Time series data for gas funace and sewage treatment processes are used to evaluate the performances of the proposed rule-based fuzzy modeling.

This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with high-order lags and dead-times.

In this paper, the hardening depth in Laser surface hardening process is estimated using a multilayered neural network. Input data of the neural network are surface temperature of five points, power and travelling speed of Laser beam. A FDM(finite difference method) is used for modeling the Laser surface hardening process. This model is used to obtain the network's training data sample and to evaluate the performance of the neural network estimator. The simulational results showed that the proposed scheme can be used to estimate the hardening depth on real time.

In this paper, we modify a multiple target angle tracking algorithm presented by Sword et al.. The predicted estimates, instead of the existing estimates, of the target angles are updated by the most recent output of the sensor array to improve the tracking performance of the algorithm for crossing targets. Also, the least square solution is modified to avoid abnormally large angle innovations when the target angles are very close. The improved performance of the proposed algorithm is demonstrated by computer simulations.

In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

This paper describes a on-line monitoring and fault diagnosis system designed for the automation of a medium-size concrete plant. The system is based on the structure of a hardware system of data acquisition and a personal computer. Simulation results are presented to illustrate the system operation. It applies the preconstructed rules to the plant data for the diagnosis of weighing processes.

In this paper, two diagnosis algorithms using the simple fuzzy, cognitive map (FCM) that is an useful qualitative model are proposed. The first basic algorithm is considered as a simple transition of Shiozaki's signed directed graph approach to FCM framework. And the second one is an extended version of the basic algorithm. In the extension, three important concepts, modified temporal associative memory (TAM) recall, temporal pattern matching algorithm and hierarchical decomposition are adopted. As the resultant diagnosis scheme takes short computation time, it can be used for on-line fault diagnosis of large scale and complex processes that conventional diagnosis methods cannot be applied. The diagnosis system can be trained by the basic algorithm and generates FCM model for every experienced process fault. In on-line application, the self-generated fault model FCM generates predicted pattern sequences, which are compared with observed pattern sequences to declare the origin of fault. In practical case, observed pattern sequences depend on transport time. So if predicted pattern sequences are different from observed ones, the time weighted FCM with transport delay can be used to generate predicted ones. The fault diagnosis procedure can be completed during the actual propagation since pattern sequences of tvo different faults do not coincide in general.

In this paper, a fault-tolerant controller using duplex processors has been designed and implemented. The PI controller is adopted as the control algorithm and the fault-tolerant control system is implemented by two single chip processors(MCS-96). Performances of the control system designed here have been shown via a simulation with application to a pitch channel autopilot.

This paper proposes a method of automatic function test for parts mounted Printed Circuit Board. For this purpose, we designed a Data Acquisition Equipment, PC interface card and inspection software. The experiment was done for the coffee vending machine and its result was good.

In this paper, for detection and isolation of instrument and process faults related with steam generator(S/G) in nuclear power plant, two types of observers are designed based on the linearized dynamic model of S/G : a bank of Dedicated Observers (DOS) for instrument faults detection and a bank of Unknown Input Observers(UIO) for process faults detection. And then, they are combined to decide which one between the above two faults occurs. In principle, the failure in ith instrument(process) can be isolated by monitoring the error between the ith output and its estimation obtained from the ith DOS(UIO). It is shown via computer simulations that the present scheme is feasible in finding out the source of a fault.

The integration of deburring robots into product quality and productivity impact the industrial. In this paper the intelligent system of robotic deburring is proposed integrated with robot system, image processing system, force sensor system and host PC. The size, position, recognition of burr is determined by the information that the image processing system processed. The feed velocity of cutting tool is controlled by the information that the force sensor system processed. The integration of these information can remove the uncertainty of the information of deburring on the cutting path. The result of these technologies is useful for the development of the factory automation and automatic inspection equipments.

In this paper, we develop the basic robot commands on the level of VAL robot language and the integrated environment software of the robot management system to give users an easy way of programming and running the robot. The developed software is designed to support Korean language and to be run by the pop-up menus for programming commands and inputs. Geometrical and dynamical features can be viewed on a computer monitor by graphics and the taught works can be interfaced with a computer and controllers.

In this paper, the arc welding robot controller using a touch sensor and a arc sensor is presented. The controller is composed of robot controller parts for moving torch, and arc welding controller for welding and tracking. In the controller, an compensated data is generated to control robot trajectory and seam tracking by the arc sensor function. The data is obtained by integration of arc current. Experimental results are presented confirming the controller performance.

An articulated, multifinger mechanical hand can carry out grasping and manipulation operations on objects of different type and shape. In this paper the architecture of the mechanical hand is presented. Joints are driven by two antagonist tendons. Strain gauges are used to derive tendon tensions, and located in the palm of the hand. Angular defection of the joints is measured by Hall effect sensors attached to the joints. A multiprocessor-based architecture for controlling the hand is illustrated.

In this paper, a parallel link typed wrist is developed for robotic precision assembly. The developed wrist can make the corrective motion required for compensating lateral and tilting errors. The mechanism of this wrist is one example of a motion simulator generating 6 DOF motion in space by 6 actuators connected in paralle. To make the wrist more compact, miniature DC motors containing reduction gears and servo system were used. The parallel link architecture enables a high positioning accuracy and high nominal load capacity. In this study, inverse kinematic problem is solved by using a Denavet-Hartenberg method and a simulational result about workspace of the proposed parallel mechanism is obtained.

We use three sensors such as a vision sensor, a proximity sensor, and a force/torque sensor fused by fuzzy logic in a peg-in-hole task. The vision and proximity sensors are usually used for gross motion control and the information is used here to position the peg around the hole. The force/torque sensor is used for fine motion control and the information is used to insert the peg into the hole precisely. Throughout the task, the information of all the three sensors is fused by a fuzzy logic controller. Some simulation results are also presented for verification.

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.

In an underwater vehicle, the navigation error is mostly caused by the initial misalignment, the bias of a gyro and an accelerometer, and the sea current. Therefore, it is important that these error sources are estimated and compensated in order to reduce the navigation error. In this paper, the E.M.Log aided SDINS is designed by using the E.M.Log which measures the forward velocity of a vehicle. And the system error state equation and the measurement equation are derived and the suboptimal Kalman Filter is established for this aided SDINS. The simulation result showed that this had an important role in estimating and compensating these error sources, thus reducing the navigation error of an underwater vehicle.

In this paper, we formulate Kalman filter for calibration of strapdown inertial measurment unit(SDIMU) on navigation system level and analyize its performance by covariance simulation method. It has been shown that the calibration method suggested in this paper is not largely influenced by accuracy of a mounting axis alignment required in calibration of SDIMU on IMU level.

In this paper, the navigation computer design of RPV(remotely piloted vehicle) using GPS is investigated, and its hardware and software structures are described. The proposed hardware adopts the common PC configuration by using 5016A micro PC card and software is divided into several modules such as navigation module, guidance module and control module, etc. The performance of the navigation computer is verified through PILS(process in the loop simulation).

In this paper, the IPE(Iterative Parameter Estimation) methods for the nonlinear measurements are proposed. The IPE methods convert the problems of the parameter estimation for the nonlinear measurements to that of the solution of the nonlinear equations approximately and use several iterative numerical solutions, such as fixed points theory, Newton's methods, quasi-Newton's methods and steepest descent techniques. the IPE methods for the nonlinear measurements-in the case of the error estimation for the inertial navigation systems are simulated, and it is found that the estimation errors for the nonlinear measurements decrease rapidly and converge to almost that of the linear LSE(Least Squares Estimation) when the IPE methods are applied.

The paper discusses the problem of computing coarser observation functions in supervisory control of discrete event systems. It is shown that when a supervisor that realizes a given language L has certain properties, L-realizability of a coarser observation function is equivalent to control-compatibility of the states in some subsets of the state space of the supervisor. This characterization is then used to devise an iterative procedure of computing coarser L-realizable observation functions, where supervisor reduction and L-realizability verification of an observation function are performed at each iteration.

A reduction method of GSPN (generalized stochastic Petri net) is proposed. A GSPN is basically a SPN (stochastic Petri net) with transition a that are either timed or immediate. Then the proposed method is defined on the basis of the dynamic behavior and the structure of the net. The reduction preserves the properties such as liveness, boundedness, and allows easy analysis of the GSPN.

This paper presents an efficient solution for a class of forbidden state problems by introducing a cyclic timed controlled marked graphs (TCMG's), a special class of timed controlled Petri nets (TCPN's) as a model of a class of discrete event systems (DES's). The state feedback control is synthesized, which is maximally permissive while guaranteeing the forbidden states will be avoided. The practical applications or tire theoretical results for an automated guided vehicle (ACV) coordination problem in a flexible manufacturing facility is illustrated.

Automatic Assembly Systems(AAS) are a class of systems exhibiting concurrency, asynchronicity and distributedness, and can be modeled by Petri Nets. In this paper, we design two types of configuration of part-assembly system in the car manufacturing line, as an example of AAS. And, we make a modeling the system by utilizing Extended Petri Nets, simulation as varying machine parameters, and analysis of operation status. These enable to present the information of optimal status and various problems occurring in the system for achieving high production rate.

For a fast evolution, a memory-based implementation of a petri net is discussed. A sub-class petri net model called B-petri net is suggested to make a memory-based implementation feasible in a large size application. The suggested B-petri net is a binary-petri net since only a binary-typed decision, fork and join are allowed. The application of a B-petri nt is focused to a SFC(sequential function chart) program. The memory requirement, speed and computational load are compared with a petri net when they are implementated by a memory-based method.

A hybrid system contains both continuous variables and discrete event components. This paper presents the new control architecture for hybrid systems, which consists of a conventional controller for the continuous-time variable of the system, a supervisor for discrete event components of the system, and an interface for link between the controller and the plant. The presented controller is suitable for the system operating at the different operating conditions or for system being changing the plant model by enabling and disabling discrete events. This paper shows that the presented controller is better than the conventional controller.

본 연구에서는 객체지향 개념과 분산형 문제해결 방법의 장점을 혼합한 FMS 생산현장통제 시스템을 제안하였다. 제안된 시스템은 FMS의 모든 구성요소를 지능적인 객체로써 표현하고, 객체들간의 Bidding 과정을 통하여 생산 현장의 상태변화에 대응해 나가는 구조를 가지고 있다. 실험 결과, 제안된 시스템은 기존의 Dispatching rule에 비하여, job의 시스템내 체류시간이 감소하며 기계부하가 평준화되는 현상을 나타내었다.

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

In this paper, the new M/T method for motor speed detection is proposed. This method can be able to reduce the dead time compared with it when Ohmae's M/T method is implemented. And the comparsion of the dead time length between the Ohmae's method and the proposed method is analyzed quantitatively. Actually we implemented the new proposed M/T method using the hardware and software and verified the effectiveness of the proposed M/T method.

In this paper, we present the voltage source algorithm for high speed and low torque ripple operation of a switched reluctance motor (SRM). The SRM has simpler structure than the traditional dc or ac motor. It has a high starting torque and can be operated in the wide range of speed. So it can be applied to various areas. But the SRM has some difficulties in driving circuit and controller due to the large inductance variations. In this study, in order to produce the low torque ripple and the high speed operation, a voltage source algorithm is proposed. We showed the good performance of the proposed controller through simulation and experiment.

The low speed control of a servo motor using instantaneous speed detection method is described. To estimate the instantaneous speed from the average speed, the speed estimator of the first or second order is used. We confirm that these estimatorsimprove the speed control performance of a servo system with experiments.

In this paper, a new automatic cardiac output control algorithm without any pressure sensors for the motor-driven electromechanical total artificial heart(TAH) was developed using motor current information. In the previous studies, many transducers were utilized to obtain informations of hemodynamic states for the automatic cardiac output control. But. such automatic control with sensors has some problems. To solve these problems, I proposed a new "sensorless" automatic cardiac output control algorithm providing the adequate cardiac output to the time-varying physiological demand without right atrial collapse. In-vitro tests were performed to evaluate the performance of a new algorithm and it satisfied the basic three requirements on the pump output response through the mock circulation tests.

Generally machine tools can be divided into three components : NC Controller, the electrical drives and the mechanical transmission elements. For high speed, high precision machining, high performance control of servo system must be accommodated and one must carefully define the interface among three components. In this paper, we suggest a way to assist future development of CNC controller by investigating the characteristics resulting from different interface between CNC controller and servo system.

A rule based fuzzy expert system to self-tune PID controllers is proposed in this paper. The proposed expert system contains two rule bases, where one is responsible for "Long term tuning" and the other for "Incremental tuning". The rule for "Long term tuning" are extracted from the Wills'map and the knowledge about the implicit relations between PID gains and important long term features of the output response such as overshoot, damping and rise time, etc., while 'Incremental tuning" rules are obtained from the relations between PID gains and short term features, error and change in error. In the PID control environment, the proposed expert system operates in two phases sequentially. In the first phase, the long term tuning is performed until long term features meet their desired values approximately. Then the incremental tuning tarts with PID gains provided by the long term tuning procedure. It is noticeable that the final PID gains obtained in the incremental tuning phase are only the temporal ones. Simulation results show that the proposed rule base for "Long term tuning" provides superior control performance to that of Litt and that further improvement of control performance is obtained by the "Incremental tuning'.ance is obtained by the "Incremental tuning'.ing'.

In this paper, a new PID fuzzy controller(FC) is presented. The linguistic control rules of PID FC is separated into two parts : one is e-.DELTA.e part, and the other is .DELTA.$^{2}$e - .DELTA.e part. And then two FCs employing these rule base individually are synthesized. The control input to the process is decided by taking weighted mean of the outputs of two FCs. The proposed PID FC improve the transient response of the system and gives better performance than the conventional PI FC.

In this paper, we propose the Fuzzy Neural Controller with a Self-Organizing Map based on the fuzzy relation neuron. The fuzzy ndes expressing the input-output relation of the system are obtained by using the fuzzy relation neuron and updated automatically by means of the generalized delta rule. Also, the proposed method has a capability to express the knowledge acquired from the input-output data in form of fuzzy inferences rules. The learning algorithm of this fuzzy relation neuron is described. The effectiveness of the proposed fuzzy neural controller is illustrated by applying it to a number of test data sets.

In this paper, fuzzy-neural network is proposed to identify the Activated Sludge Process(A.S.P) in sewage treatment such as "IF-THEN" type fuzzy rules and using various learning methods and improved complex method, the performance index of the identified model is improved. The proposed FNN has the neural network structure of which the connection weights have particular meanings for obtaining fuzzy inference rules and for tuning membership functions. And based on the identified model, graphic simulator which can analize nonlinear characteristics of A.S.P and generate control strategy for A.S.P is being developed.developed.

Robots working in the multiple robot system can perform the variety of tasks compared to the single robot system, while they are subject to the various tight constraints such as the precise coordination and the mutual collision avoidance during the task execution. In this paper, we provide an algorithm and graphical verification for collision avoidance between two robots working together. The algorithm calculates the minimum time delay for collision avoidance and the graphical verification is performed through the 3-D graphic simulator.

A velocity planning method is proposed that ensures collision-free and minimal delay-time motions for two robotic manipulators and auxiliary equipments. Additional path, which makes robot start with possible largest speed, is added to the original prescribed path of one of two robots, and this running start along the additional path reduces delay time introduced to avoid collision between the robots and therefore reduces total traveling time.

An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We use the view-time concept, especially the adaptive view-time. First. we introduce the adaptive view-time and analyze its properties. Next, we propose a view-time based motion planning method. The proposed method is applied and simulated for the collision-free motion planning of a 2 DOF robot manipulator. We simulate the robot motion under several different view-time systems. Generally, the motion planning with the adaptive view-time systems has some advantages over that with the fixed view-time systems.

This paper present a sensor based obstacle avoidance method which is based on a VFH(Vector Field Histogram) method. The basic idea of obstacle avoidance is to find a minimum obstacle direction and distance. From the minimum sonar index and the target direction high level system determine steering angle of mobile robot. The sonar sensor system consists of 12 ultra sonic sensor, and each sensor have its direction and safety value. This method has advantage on calculation speed and small memory. This method is implemented on indoor autonomous vehicle'ALiVE-2'.

The role of a robot becomes more important as factory automation is widely spread in the manufacturing industry. An off-line program system has been required for uninterruption of production lines because it can save cost and time spent in adjusting a robot to a new workcell. The objective of this paper is to develop our own OLP system for a SCARA type FARA robot with four axes. Three-dimensional graphic results are presented for the case when the robot is simulated using the computed torque method with a PD controller and the continuous path trajectory planning.

Guidance commands for attitude controlled missiles inevitably take the form of attitude angle commands. On the other hand, many guidance laws compute the accelerations required to achieve their goals. Therefore some integrators must be in use for the attitude controlled missiles to implement the guidance laws. Naturally, the use of the integrator raises the problem of choosing a proper initial value. In this paper, we compute the integrator initial value which minimizes the terminal miss and show that if the total flight time of the mission is long enough, the "optimal" initial value becomes some multiple of the initial heading error or of the given impact angle to the target. We demonstrate the validity of the analysis by showing some linear and nonlinear simulation results.n results.

CADET is used to analyze the performance of the missile. Miss distance is calculated for a given lateral fin force saturation level due to the aerodynamic characteristics, target acceleration, and glint and fading noises which is assumed as Gaussian noises. As .alpha.-.betha. filter is studied to attenuate the noises, the results are compared with those of without filter. For the easy simulation, the transfer function of a discrete .alpha.-.betha. filter is converted into the continuous model. Simulation results show that the results of CADET simulation is similar to those of Monte-Carlo simulation. Moreover CADET is the better in computing time demand.

The instrumentation system is the most important aspect of a flight test program. It is the means by which the objective of a flight test, the production of accurate, useful data, is achieved. An instrumentation system consists of everything required to sense, condition, and record all parameters of interest The task of a flight test engineer is to select a system that is adequate to obtain all needed data, but not complex, expensive, and heavy than the situation demands. In this paper, the primary factors that determine the design of an instrumentation system are discussed.

A HILS(Hardware-In-the-Loop Simulation) technique for an IR guided weapon is proposed. The IR HILS facility functions as a testing unit for a missile guidance and control system to evaluate target acquisition, tracking, and countermeasure performance. The configuration of IR HILS facility, modeling technique of an IR environment including target, background and countermeasure, and test and evaluation procedure are included.

In this paper we proposed the digital implementation of an $H^{\infty}$-optimal controller using lifting technique and $H^{\infty}$-control theory. The discrete controller is obtained through iterative adjustment of sampling time and weighting function, which can ber performed by computing the L$_{2}$-induced input to output norm of the sampled-data system with bandlimited exogenous input. The resulting sampled-data bandlimited exogenous input. The resulting sampled-data system is stable and the performance including inter-sampling behaviour of the hybrid system can be also optimized.d.

The aim of this paper is to analyze via computer simulation the robust performance of TDF(Two Degree of Freedom) H.$_{\infty}$ controller for uncertain systems having parameter uncertainty. We apply the TDF H$_{\infty}$ controller to autopilot design. We evaluate the robust performance of the TDF H$_{\infty}$ controller for uncertain systems and present the guaranteed bound of robust performance via computer simulation.on.

This paper deals with structured singular value and mixed sensitivity problem for robust performance. We derive the sufficient condition that mixed sensitivity problem satisfies structured singular value in robust performance problem. And we show the bound of perturbation between structured singular value and norm of mixed sensitivity functions.

This paper presents an improved algorithm which enables to find a suboptimal $H^{\infty}$ controller. In the $H^{\infty}$ control problem with output multiplicative uncertainty, the Glover-Doyle algorithm has sorne constraints for the standard plant. The proposed algorithm removes them by reformulating the standard plant. We show the validity of this algorithm by investigating the variation of norm-bound.d.

In MIMO design, input and output units are different from each other. By this reason, the effect of larger units to smaller one is not trivial and there is no method of proper scaling, optimal scaling. In this paper, robust stability of MIMO LQG/LTR design are analised when the plnat inputs and outputs are scalled. The upper bound of model error to guarantee the robust stability is obtained, and gain margin and phase margins are computed with respect to scalling matrices.

In this paper, a robust and reliable H$_{\infty}$ control problem is considered for linear uncertain systems with time-varying norm-bounded uncertainty in the state matrix, which performs well despite of actuator outages. Using linear static state feedback and the quadratic stabilization with H$_{\infty}$-norm bound, a robust and reliable H$_{\infty}$ controller is obtained that stabilizes the plant and guarantees an H$_{\infty}$-norm bound constraint on disturbance attenuation for all admissible uncertainties and normal state as well as faulty state of actuators. It provides a sufficient condition for robust and reliable stabilization with H$_{\infty}$-norm bound. Reliability is guaranteed provided actuator outages only occur within a prespecified subset of actuators.tors.

A heavy load driving system for the gun laying control is designed with the analysis of performance in pointing accuracy and speed. To eliminate the firing noise and high frequency system noise, a .PI. filter is implemented in conjunction with the PI velocity control. To incorporate the gunner's commands in the PID position control loop easily, a .mu.-processor is utilized in the position control loop. Main difficulties in the heavy load driving system exist in the design of motor drivers and heat sinkers. With an appropriate design of the motor drivers and heat sinkers, the performance of the gun laying system is analyzed by the simulation.

본 연구에서는 저속에서도 시스템의 자세 제어가 용이하게 하기 위하여 추진기 뒤에 제어판이 위치하도록 설계하였으며, 일반 서보 시스템과는 달리 무게와 공간 제약이 크고, 제어판 운동에 따른 외란 등록성의 변화가 심하므로 push-pull 형태의 소형, 고출력 편로드 복동 복수 실린더의 작동기를 설계하였다. 또한 일반적으로 서보밸브와 작동기는 일체형으로 설계되나 본 시스템의 공간상 심한 제약으로 인하여 서보밸브와 작동기를 분리하는 방법으로 구조설계를 하고 그 사이 유로는 매니폴드식으로 하여 동력전달을 하였다. 설계된 구동장치를 실제 정밀제작하여 실험을 수행하였으며, 시뮬레이션 결과와 실험에 의하여 얻어진 결과를 비교 분석하여 설계의 타당성 및 시스템의 성능을 검증하였다. 고속 수중운동체에 대하여 저속에서 자세제어를 용이하게 하고, 제한된 좁은 설치공간의 문제점을 해결하기 위하여 1) 추진기 후미에 독립된 4개의 상, 하, 좌, 우 제어판 설치 2) 서보밸브는 몸체에, 작동기는 Tail Tube에 분리 작동 설계 3) 소형의 편로드 복동 복수 실린더로 설계 구성된 유압식 구동장치는 시뮬레이션과 실험 결과를 통하여 시스템의 타당성을 입증하였다. 그러므로, 개발한 구동장치는 저속에서도 큰 제어력으로 자세 제어가 용이하기 때문에 얕은 수심에서 발사시 예상되는 위험 요소를 상다ㅇ 개선 시키므로써 운용범위의 다양화를 가져 올것으로 기대된다.

In order to hold a underwater vehicle at a depth, we can modulate buoyancy that acts on the underwater vehicle. In this research, by using a ballon, we was able to generate buoyancy that could control depth in which vehicle was operate. And in order to control flux of air that was flowed in balloon, we used solenoid valve, relief valve and so on. We derived differential equations of volume of balloon, pressure of inside of balloon, dynamic of underwater vehicle, and air flux for the simulation and linearized these differential equation. So we designed LQG/LTR controller, and applied the controller to nonlinear system. Through the simulation, we compares the nonlinear system with the linear system and investigated the operation of solenoid valve.

The first objective of this study is to derive an automated method that minimizes the number of spline regions and optimizes the locations of the knots to provide and adequate fit of a given nonlinear function. This has been accomplished by the development of the Optimal Spline Method discussed herein. The second objective is to apply the derived automated method to an important application. This objective has been accomplished by the successful application of the Optimal Spline Method to ship classification.

Generally the method of depth controlling is classified into buoyancy control and thrust control. In this study, we employed thrust control system. And mathematical modeling and computer simulation are performed in order to design auto depth control system for underwater vehicle. Consequently, the specifications of components are determined, and the performance of system is analyzed.

In this paper, two side-attack guidance laws for an underwater vehicle are considered. In order to find the guidance command, we first make use of the optimal guidance law with terminal impact angle constraint. Secondly, the optimal solution of tracking problem is used. This paper shows some brief theory which is used in deriving the side-attack guidance laws, and the method of computing these guidance laws. Simulations on underwater vehicle for a constant moving target prove that the suggested side-attack guidance laws have enhanced side attack performance over the optimal guidance law with miss distance weighting only. Furthermore, from simulation results. we conclude that the guidance law using the optimal solution of tracking problem is more efficient for the side-attack guidance than the optimal guidance law with terminal impact angle constraint.

When modeling an underwater vehicle uncertainty arises in the presence of unsteady flow. It is difficult to include the uncertainty in the model and is therefore desirable to investigate robust controller design methods for the underwater vehicle. In the paper two robust control methods are applied for the underwater system. One is standard H$_{\infty}$ control and the other is time-varying sliding mode control with modified saturation function. Suboptimal design parameters for H$_{\infty}$ control and design parameters for time-varying switching surfaces are provided. Simulations and comparison are carried out.t.

A new robust sliding mode controller is formulated for the tip position control of a single-link flexible manipulator with parameter variations. After establishing the plant model characterized by a noncollocated uncertain control system, a sliding surface which guarantees stable sliding mode motion is synthesized in an optimal manner. The surface is then modified to adapt arbitrarily given initial conditions. A discontinuous control law associated with the modified surface is designed by restricting that velocity state variables are not available from direct sensor measurements. Using the proposed control law favorable system responses are accomplished through shortening the reaching phase of state trajectory without increasing maximum control torque as well as undesirable chattering. Furthermore, a low sensitiveness to uncertainties is obtained from inherent salient properties of the proposed control system. Computer simulations are undertaken in order to demonstrate these superior control performance characteristics to be accrued from the proposed methodology.

In this paper, control of a planar two-link structurally flexible robotic manipulator executing unconstrained and constrained maneuvers is considered. The dynamic model, which is obtained by using the extended Hamilton's principle and the Galerkin criterion, includes the impact force generated during the transition from unconstrained to constrained segment of the robotic task. A method is presented to obtain the linearized equations of motion in Cartesian space for use in designing the control system. The linear quadratic Gaussian with loop transfer recovery (LQG/LTR) design methodology is exploited to design a robust feedback control system that can handle modeling errors and sensor noise, and operate on Cartesian space trajectory errors. The LQG/LTR compensator together with a feedforward loop is used to control the flexible manipulator. Simulated results are presented for a numerical example.

Nonlinear equation of motion of the flexible manipulator are derived by the Lagrangian method in symbolic form to better understand the structure of the dynamic model. The resulting equations of motion have a structure which is useful to reduce the number of terms calculated, to check correctness, or to extend the model to high order. A manipulator with a flexible 4 bar link mechanism is a constrained system whose equations are sensitive to numerical integration error. This constrained system is solved using the null space matrix of the constraint Jacobian matrix. Singular value decomposition is a stable algorithm to find the null space matrix.

In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

화학 공정에서의 이상 진단 시스템 개발 및 응용에 대한 연구는 지난 5년간 많은 발전이 이루어졌다. 화학 공정의 본질적인 특성으로 대형 시스템, 비선형 특성, 모델링 자체의 어려움, 공정 변수의 large dead time 및 복잡한 인과 관계등을 들수 있으며, 이러한 어려움에도 불구하고 적절한 이상 진단 시스템의 중요성을 인식하여, 초기에는 주로 rule-based approach가 도입되어 현장에서의 조업에 많은 도움을 주었었다. 그러나 개발 기간의 단축화, 개발 과정의 표준화 뿐 아니라 개발된 시스템 자체의 일관성 등을 위하여 체계적인 접근 방법이 필요하게 되었으며, 그중 지식 베이스 합성 문제는 그 동안 활발하게 연구되어 오고 있는 분야이다. 이에 본 연구에서는 기호화된 정성적인 정보를 얻기위한 기존의 실험 방법의 한계를 극복하고자 동적 모사를 이용하여 정량적인 정보로부터 정성적인 정보를 생성시키는 방법론에 대해 연구하였다. CSTR(Continuous Stirred Tank Reactor)에서 나타날수 있는 이상의 종류에 대한 동적 모사를 수행하여 이상 진단 시스템을 위한 지식이 생성되는 과정을 보였다.

Grinding in the cement industry is a very energy-exacting process, therefore it is essential that these systems should operate with the highest possible efficiency. But, Cement grinding process is a complicated nonlinear system with large dead time, very noisy signal and many stochastic disturbances. So, it is difficult to develope mathematic process model. This paper presents correlation analysis of process variables and construction of experimental model for a ball mill grinding process.

A scheme of dynamic optimization for batch reactor his been developed and applied to a semi-batch esterification reactor. To obtain optimal operating conditions for the given semi-batch reactor system with complex reaction kinetic and process constraints, a general nonlinear programming solver and finite element techniques have been introduced. The optimization results for the complex reactor system have been compared with those of Kumar et al. [1984] to show better optimization performance. The proposed optimizing scheme has been applied to the free end time problem to obtain the realistic operating condition. The results can supply valuable information for economic operation of the given batch esterification reactor.

This paper presents a fault detection strategy that discriminates the faulty sensor and that detects the component fault using a bank of observers for the system in which sensor fault and component fault can occur simultaneously. Observers as many as the number of measurements are designed, and each observer uses measurements excluding sequentially one measurement, to estimate the state variables. The faulty sensor can be found out by comparing each state variable from different observer. Next, component fault can be detected by using measurements from the sensors excluding the faulty sensor. The suggested strategy is applied to a nonisothermal, series reaction with unknown reaction kinetics in a CSTR. This strategy is found out to perform well even in the case that the sensor and component fault occur simultaneously. Since each observer is designed to be independent of reaction kinetics, this strategy is not affected by the model uncertainty and nonlinearity of the reaction kinetics.

The heat of reaction has been estimated from heat balance relationships around the reactor. The heat balance equations were formulated with the assumptions that the reactor temperature is uniformly distributed and the jacket temperatures are axially distributed. We have obtained the temperature distribution of jacket contents by FDM. And then, we have rearranged the heat balance equations so that the heat of reaction can be estimated from the finite number of temperature measurements, i.e., temperatures of the reactor contents, at the jacket inlet and outlet, respectively. The proposed method for reaction heat estimation on were applied to industrial batch reactors ; one is ABS polymerization reactor and the other is SAN polymerization reactor. We have also examined the variation of overall heat transfer coefficients for the reactors during reaction.

From the power plants in a steel plant, environment pollutants such as SOx, NOx, CO are emitted by the combustion reaction between the fuels those are by-product gases and oil. To reduce the amounts of the pollutants, it must be important that build the predictive models for the emission of the pollutants. In this paper, the model that predict the amount of future fuel consumption and the model that predict the amount of generated pollutants for the used fuel amounts is developed by using Gibb's free energy minimization method with the temperature correction techniques and neural network back propagation method. For some data set, the calculation results from this models are compared with the real emission amounts of SOx, NOx and result of the calculation by the ASPEN plus which is a commercial software. The result from this model is better than the result by ASPEN plus for this problem.

In this paper, a heuristic procedure is presented which first determines the positions of adding storage tank. Then a nonlinear programming is formulated to obtain their optimum size. Flexible utilization(shared equipment) of storage tank is suggested. The effectiveness of this method is verified by solving two literature problems.

This paper presents the aircraft autopilot system with a pre-designed gain schedule. It is mainly consisted of the parameter estimation end the autopilot system design. For off-line parameter estimation, leastsquare methods are investigated. The design of a controller is done in frequenced domain using classical control method and it is designed to satisfy the predetermined requirement such as time constant and transient response. Finally, it is compared with a optimal regulator.

In this paper, a neural network is appled to design a lateral autopilot for airplanes. Linearized lateral dynamics is used in training the neural network controller and verifying the performance as well. To train the neural network, back propagation algorithm is used. In this training, no information about the dynamics to be controlled except sign and rough magnitude of control derivatives is needed. It is shown by computer simulations that the performance and stability margin are satisfactory.

In this paper, a model reference adaptive control scheme is applied to the normal acceleration controller for missiles with nonminimum-phase characteristics. The proposed scheme has an auxiliary compensator, an identifier of plant parameters and a feedback control law. First, plant parameters are estimated by the identifier and based the parameter estimates the coefficients of the compensator are calculated so that the estimated plant model with the compensator becomes minimum-phase. In this calculation, Nehari Algorithm is used. Parameters of the control law are then updated so that the extended plant model follows the given reference model. It is shown that the performance of the designed controller is satisfied via computer simulations.

In this paper, the Monte-Carlo method was applied to the controller robustness evaluation problems with respect to the uncertainty of critical plant parameters. The plant studied is a aerial vehicle. The-variable parameters are nondimensional stability derivatives, inertias. The nominal nondimensional stability derivatives ,were obtained from wind tunnel test. Also the nominal inertia parameters were calculated from the mass distribution along the vehicle axes. But the parameters obtained from the test or calculations are at best probable and always contain some uncertainties which one can not figure out. So some kinds of robustness evaluation method should be applied. The parametric robustness of the designed classical controller evaluated by the method turned out to be satisfactory.

Recent researches on control theory enable nonlinear state feedback which is more closer to real system without approximation. To apply nonlinear control theories, all state variables should be measured or estimated. In this paper, a technique of designing nonlinear state observer for a particular class of nonlinear system is presented. The result is applied to an aircraft model to prove the convergency of observation error.

In general, systems contain uncertain elements in the real world; these may be parameters, constant or varying, that are unknown or imperfectly known. When the uncertainty is assumed to satisfy the matching condition and to be cone-bounded, Y.H. Chen[81 proposed an adaptive robust control algorithm which introduced adaptive scheme for a design parameter into robust deterministic controls. In this paper, the above control algorithm is applied to the position tracking control of 2 DOF direct drive SCARA robots, and simulation and experimental studies are conducted to verify the control algorithm and to evaluate control performance.

This paper presents an nonlinear observer scheme for flexible joint robot manipulators. This nonlinear observer scheme is based on the sliding mode method. Sliding controllers have recently been shown to feature excellent robustness and performance properties for specific classes of nonlinear tracking problems. Dynamic equations of flexible joint robot manipulators are derived from the Euler-Lagrange equations by forming the corresponding Lagrangian. Simulation results are presented to show the validness of the proposed nonlinear observer scheme.

In this paper, a robot controller that has a real time-multitasking OS (Operating System) is developed. It can do given jobs in realtime, so its effectiveness is increased. The controller has several CPU boards, and it is needed to communicate among these boards. For that reason, it is adopted VME bus system and VMEexec OS that can process multiprocess in realtime. Multiprocess includes robot language edit process, vision process, low level motion control process, and teach process in higher layer. And dynamics, kinematics, and inverse kinematics that require realtime calculation are included in lower layer.

Neural networks are used in the framework of sensorbased tracking control of robot manipulators. They learn by practice movements the relationship between PSD ( an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple backpropagation networks one of which is selected according to which division (corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very fast training and processing implementation required for real time control.

A new robust control law is proposed for uncertain rigid robots and two composite robust control laws for flexible-joint manipulators which contain uncertainties. The uncertainty, is nonlinear and (possibly fast) time-varying. Therefore, the uncertain factors such as imperfect modeling, function, payload change, and external disturbances are all addressed. Based only on the possible bound of the uncertainty, a robust controller is constructed for the rigid counterpart of the flexible-joint robot Some feedback control terms are then added to the robust control law to stabilize the elastic vibrations at the joints. To show that the proposed composite robust control laws are indeed applicable to flexible-joint robots, a singular perturbation approach and the stability study based on Lyapunov function are proposed.

The bead shape in high frequency electric resistance (HER) pipe welding gives important information ons judging current welding state. In most manufacturing process, the heat input is controlled by skilled operators observing color and bead shape. We proposed the bead shape monitoring system in HERW pipe process by using structured light beam. We reconstructs 3-D shape of bead from the measured data, and compare this shape with real 3-D shape obtained by coordinate-measuring machine. This experiment results show that the proposed system can monitor the bead shape with good accuracy.

This article presents an approach to estimate the general 3D motion of a polyhedral object using multiple, sensory data some of which may not provide sufficient information for the estimation of object motion. Motion can be estimated continuously from each sensor through the analysis of the instantaneous state of an object. We have introduced a method based on Moore-Penrose pseudo-inverse theory to estimate the instantaneous state of an object. A linear feedback estimation algorithm is discussed to estimate the object 3D motion. Then, the motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown object. The techniques of multisensor data fusion can be categorized into three methods: averaging, decision, and guiding. We present a fusion algorithm which combines averaging and decision.

This paper introduces a PC-based image data processing unit that is composed of preprocessor board and main processor board; The preprocessor contains Inmos A110 processor and efficient H/W architecture for fast mask/logic operations at the speed of video signal rate. It is controlled by the main processor which communicates with the host PC. The main processor board contains TI TMS320C31 digital signal processor, and can access the frame memory of the processor for extra S/W tasks. We test 3*3, 5*5 masks and logic operations on 386/486/DSP and compare the result with that of the proposed unit. The result shows ours are extremely faster than conventional CPU based approach, that is, over several hundred times faster than even DSP.

This paper presents a Bin-Picking method in which robot recognizes the positions and orientations of jumbled objects placed in a bin, then picks up distinctive objects from the top of the jumble. The jumbled objects are recognized comparing the characteristics extracted from stereo images with those in the CAD data. The 3-D information is obtained using the bipartite-matching method which compares image of one camera with the image of the other camera Then the robot picks up the object which will cause the least amount of disturbance to the jumble, and places it at a predetermined place. This paper contributes to the basic study of Bin-Picking, and can be used in an automatic assembly system without using part sorting or orienting devices.

When the error path can be modeled as a pure delay, an adaptive algorithm for slowly time varying system is proposed to minimize the sound pressure level. This algorithm makes it possible to use the fittered-x LMS algorithm with on-line delay modeling of the error path. Another simple adaptive algorithm for pure tone noise is proposed which eliminates the cross term in the multiple error filtered-x LMS algorithm.

In this paper, a method of using a look-up table for a fuzzy logic controller is proposed. A look-up table is designed for a fast inference. An algorithm for an inference is developed with a view to decrease execution time. The performance of the developed fuzzy controller is compared with that of the traditional one.

In this paper, we focus upon the design and applications of adaptive fuzzy-neuro controllers. An intelligent control system is proposed by exploiting the merits of two paradigms, a fuzzy logic controller and a neural network, assuming that we can modify in real time the consequential parts of the rulebase with adaptive learning, and that initial fuzzy control rules are established in a temporarily stable region. We choose the structure of fuzzy hypercubes for the fuzzy controller, and utilize the Perceptron learning rule in order to update the fuzzy control rules on-line with the output error. And, the effectiveness and the robustness of this intelligent controller are shown with application of the proposed adaptive fuzzy-neuro controller to control of the cart-pole system.

In this paper, we propose a neural network with fuzzy preprocessor not only for improving the classification accuracy but also for being able to classify objects whose attribute values do not have clear boundaries. The fuzzy input signal representation scheme is included as a preprocessing module. It transforms imprecise input in linguistic form and precisely stated numerical input into multidimensional numerical values. The transformed input is processed in the postprocessing module. The experimental results indicate the superiority of the backpropagation network with fuzzy preprocessor in comparison to the conventional backpropagation network.

Most of clustering methods usually employ the center of a cluster to assign the input data into a cluster. When the shape of a cluster could not be easily represented by the center of cluster, however, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty, a cluster is to be represented as a collection of several subclusters. And membership functions are used to represent how much input data belong to subclusters. Then the position of each subcluster is adoptively corrected by use of a competitive learning neural network. To show the validity of the proposed method, a numerical example is illustrated, where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.

In this paper, a predictive fuzzy control algorithm to supervise the elevator system with plural elevator cars is proposed and its performance is evaluated. Elevator group controller must decide the service elevator for a registered hall call to satisfy the multiple control objects. The proposed group control algorithm ensures the efficient operations of the group cars and provides the improved level of service, coping with multiple control objects and uncertainty of system state. The feasibility of the proposed control algorithm is evaluated by simulation on computer.

In this paper, we design the fuzzy logic controller(FLC) for a nonlinear multivariable steam generating unit. Based on the knowledges of operator, the self-organizing controller(SOC) - a kind of FLC - is developed and tested. Both FLC and SOC based on linguistic rules have the advantages of not needing of some exact mathematical model for plant to be controlled. Beside, the SOC modifies the existing control rules by monitoring the control performance. The computer simulations have been carried out for the 200MW steam generating unit to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

The dynamics and control of two complex column configurations (sidestream column with stripper; prcfractionater/sidestream column configuration), which are multivariable interacting and nonlinear, have been studied. A new control scheme developed by Hanand Park(1993) to deal with the nonlinear and multivariable nature of distillation processes has been applied to these complex distillation configurations. The control scheme incorporates a nonlinear wave model into a generic model control framework. An observer based on the nonlinear wave model is used to determine the profile positions of distillation column sections. The control scheme enables tight control of the profile position of each column section that leads to fast stabilization of product compositions.

It is very difficult to control batch reactor with conventional linear controller due to its severe nonlinearity. To control the nonlinearity of batch reactor, we applied with relay feedback method and SOAS. The SOAS can be designed to work quite well, but it requires engineering effect and some knowledge about the process in order to get a satisfactory performance of the closed loop system For the applications to more reliable, further studies on robustness in various situations and process noises and would be required.

An adaptive model predictive control (AMPC) strategy using auto-regression moving-average (ARMA) models is presented. The characteristic features of this methodology are the small computer memory requirement, high computational speed, robustness, and easy handling of nonlinear and time varying MIMO systems. Since the process dynamic behaviors are expressed by ARMA models, the model parameter adaptation is simple and fast to converge. The recursive least square (RLS) method with exponential forgetting is used to trace the process model parameters assuming the process is slowly time varying. The control performance of the AMPC is verified by both comparative simulation and experimental studies on distillation column control.

A multivariable learning control is designed in frequency domain. A general to of feedback assisted learning scheme is considered and an inverse model based learning algorithm is derived through convergence analysis in frequency domain. Performance of the proposed control method is evaluated through numerical simulation.

A mathematical model is developed to represent the batch reactor for free radical polymerization of PMMA The model is validated by comparing the simulation result with the experimental data. A computational scheme is proposed to determine the trajectory of the reactor temperature that will produce polymer product having the desired molecular weight distribution. For this instantaneous number average chain length and polydispersity are introduced to calculate the reactor temperature. The former is assumed to be a second order polynomial of the sum of the living and dead polymer concentrations. Various reactor temperature, trajectories are observed depending on the reactor conditions and prescribed molecular weight distributions. Fuzzy and PID control algorithms are applied to trace the reactor temperature trajectory. While the PID control gives rise to an overshoot when the trajectory changes its direction, the fuzzy controller yields a more satisfactory performance because it secures information on the trajectory pattern.

This paper presents a neuro-fuzzy modelling method that determines chemicals dosing model based on historical operation data for effective water quality control in water treatment system and calculates automatically the amount of optimum chemicals dosing against the changes of raw water qualities and flow rate. The structure identification in the modelling by means of neuro-fuzzy reasing is performed by Genetic Algorithm(GA) and Complex Method in which the numbers of hidden layer and its hidden nodes, learning rate and connection pattern between input layer and output layer are identified. The learning network is implemented utilizing Back Propagation(BP) algorithm. The effectiveness of the proposed modelling scheme and the feasibility of the acquired neuro-fuzzy network is evaluated through computer simulation for chemicals dosing control in water treatment system.

The dynamics for a two-body problem including perturbations due to nonspherical gravitation of the earth, gravitation of the sun and moon, radiation of the sun is studied. Orbit determination was performed by SVD filter. The simulation result shows that the characteristics of the satellite orbit have east-west and south-north drift. Therefore, the periodic magnitude of the control time and value in the view of the periodicity of error can be provided, and this result can be basic data to a station keeping problem with an orbit determination result.

The objective of this study is to develope a satellite dynamic simulator, which can test and analyze the performance of spacecraft attitude control, antenna pointing instruments, communication equipments and spacecraft components under the space environment. The satellite simulator can be used to predict the events such as malfunction and failure of satellites in space during operation and can be used to protect against emergencies. At first, the performance test system of attitude control is investigated which can simulate motion and verify stability of spacecraft. Our system consists of an attitude control main processor and a sub-processor including some real hardwares such as attitude sensors and actuators. In this paper, we describe the procedure of designing and manufacturing the dynamic simulator hardware, which consists of the central processor board, the sub-processor board and the sun sensor, and also communication between the components.

In this study the attitude control of the KOREASAT is investigated. The KOREASAT is a geostationary satellite and its 3 attitude angles, namely, roll, pitch and yaw angles, are stabilized by using the 3-axis stabilization technique. In the pitch control loop, the pitch attitude angle received from the earth sensor is processed in the attitude processing electronics by using PI type control logic, and the control command is sent to the momentum wheel assembly to generate the control torque by varying the wheel rate. The roll/yaw attitude control is performed by activating a magnetic torquer or by firing appropriate thrusters. The magnetic torquer interacts with the earth magnetic field to produce the control torque, and the thrusters are used to control the larger roll attitude errors. In this study dynamic modelling of the satellite is performed. And the earth sensor, the momentum wheel, and the magnetic torquer are mathematically modelled. The 3-axis attitude control logic is implemented to make the closed-loop system and simulations are carried out to verify the implemented control laws.

In this paper, the scheme of combining the orbit correction and attitude control of a 3-axis stabilized satellite is suggested. Being coupled and complimentary, it is preferable to achieve the required orbit correction and the desired attitude control simultaneously. A solution of the probes simultaneous control of orbit correction and attitude of a satellite, is obtained by solving the two point boundary value problem numerically. The first-order gradient algorithm is used to solve the numerical problem. The simulation results show that the East-West station keeping process with the combined system of an orbit correction and an attitude control is satisfactory.

In this paper, we propose a compliance control scheme using a neurofuzzzy compliance model(NFCM). as a new control paradigm for telerobot systems. A NFCM, used as a compliance controller, is composed of a fuzzy compliance model(FCM), a neural network and a low pass filter. The NFCM is trained through a reinforcement learning algorithm, and then, can generate suitable compliant motion for a given task. A series of simulations have been performed to show applicability of the proposed algorithm send it is found that the NFCM can implement suitable compliant motion for a given task through the learning procedure.

The development of fuzzy pan/tilt controller for remote handling in hostile environment is presented in this paper. In remote handling, control of the camera system is somewhat tedious and time consuming. Operators should do the two tasks of manipulating teleoperator and camera pan/tilt at the same time. By automating pan/tilt control, we expect operators could concentrate only on remote operation. When operators control camera pan/tilt they use simple linguistic rules such as "If the position of end effector on TV monitor is at the edge of the screen, control pan/tilt to display the end effector near the center of the screen." Such a rule is similar to fuzzy logic, so we used fuzzy logic controller to control camera pan/tilt. pan/tilt.

Robotic technology has been grown up conspicuously by its versatility. KAERI has been involved in one of facets of robot industry to keep abreast of rapid evolving technologies In robotic field and has launched long-term R&D plan to assure the stable nuclear energy. In this paper, the latest development status of teleoperated robot system has been presented with emphasis the configuration of overall control system with 3 dimensional graphic system that provides operators with tele-presence situation. This robot system under development, composed of master-slave arm with controller and graphic simulator, is operated by a master manipulator to enable an installation and removal operation of nozzle dam system for steam generator. Evaluation and analysis has been carried out to get optimal parameters of robot system.

In hazardous conditions, where entry of human operators is restricted, such as high radiation regions in nuclear facilities, a lot of remote inspections and remote handling tasks must be performed. In this study, the stereo imaging system has been developed and the remote handling technique, has been studied to enhance the efficiency of tele-operation. The nozzle dam handling robot is one of the most important robots applied to nuclear facility. The robot will be equipped with the developed stereo imaging system. The stereo imaging system will outstandingly improve the tele installing/removal tasks for nozzle dam.

As a part of the Department of Energy's Environmental Restoration and Waste Management Program, long-reach manipulators are being considered for the retrieval of waste from large storage tanks. Long-reach manipulators may have characteristics significantly different from those of typical industrial robots because of the flexibility of long links needed to cover the large workspace. To avoid structural vibrations during operation, control algorithms employing various types of shaping filters were investigated. A new approach that uses imbedded simulation was developed and compared with others. In the new approach, generation of joint trajectories considering link flexibility was also investigated.

The errors in machining process by CNC machining center are due to many elements, such as the delay of the servo drivers, friction and the gain mismatch between x-axis and y-axis motors and so on. We made a counter circuit to measure the output of motor encoders for the motion error analysis of a CNC machining center, and have measured the errors experimentally when the CNC performs a circular interpolation. We have also used an iterative learning method to reduce the radius errors and stick motion errors generated by the CNC machining center performing a circular interpolation. The proposed learning scheme worked well and the circle obtained has smaller error.

For a class of discrete-time nonlinear systems, an iterative learning control method is proposed and a sufficient condition is derived for the convergence of the output error. The proposed method is shown to be less sensitive to modelling errors and the uniform boundedness of the output error is guaranteed even in the presence of initial state errors. It is illustrated by simulations that the actual output converges to a desired output within the tolerance bound and convergence performance is improved by the presented method.

Because of complexity, neural network is difficult to learn. So if internal representation[1] can be performed successfully, it is possible to use perceptron learning rule. As a result, learning is easier. Therefore the method of internal representations applied to the "XOR" problem, and the "spirals" problem. And then using the above results, the structure of neural network for computing is embodied.mputing is embodied.

In this paper, we present a recursive algorithm for the auto-tuning of PID controllers by optimizing a GPC criterion. Also, we develop an intelligent PID controller by combination of a recursive algorithm together with a supervisor, that allows to adjust the main controller parameters (prediction horizon, control weighting, sample time etc.) using some simple rules which is mainly built up through relay tuning experiments. The intelligent PID controller has been implemented successfully on an IBM PC/AT and some simulation results are presented.

The error back-propagation(BP) algorithm is widely used for finding optimum weights of multi-layer neural networks. However, the critical drawback of the BP algorithm is its slow convergence of error. The major reason for this slow convergence is the premature saturation which is a phenomenon that the error of a neural network stays almost constant for some period time during learning. An inappropriate selections of initial weights cause each neuron to be trapped in the premature saturation state, which brings in slow convergence speed of the multi-layer neural network. In this paper, to overcome the above problem, Micro-Genetic algorithms(.mu.-GAs) which can allow to find the near-optimal values, are used to select the proper weights and slopes of activation function of neurons. The effectiveness of the proposed algorithms will be demonstrated by some computer simulations of two d.o.f planar robot manipulator.

There are two methods to get 3-dimensional information by matching image pair feature-based matching and area-based matching. One of the problems in the area-based matching is how the optimal search region which gives accurate correlation between given point and its neighbors can be selected. In this paper, we proposed a new area-based matching algorithm which uses edge-features used in the conventional feature-based matching. It first selects matching candidates by feature-based and matches image pair with area-based method by taking these candidates as guidance to decision of search area. The results show that running time is reduced by optimizing search area(considering edge points and continuity of disparity), keeping on the precision as the conventional area-based matching method.

This paper presents the problem of automatically recognizing embossed or molded characters which are raised from the side wall on rubber tire. In the tire image objects have approximately the same gray-value as the background and because of the tire geometry, illumination of the surface is nonhomogenous. Therefore it is difficult to recognize the raised tire character. In this paper, for describing the process of processing three steps have been proposed: 1) MIN & MAX smoothing operation filter, 2) edge detection algorithm using modified laplacian operator, 3) noise rejection. Afterwards, segmentation is done to attain characters from tire image by projection method. The recognition of the characters in the segmented image is carried out by using multilayered neural network, which is insensitive to the noise.

This paper presents a binary clustering network (BCN) and a heuristic algorithm to detect pitch for recognition of keywords in continuous speech. In order to classify nonlinear patterns, BCN separates patterns into binary clusters hierarchically and links same patterns at root level by using the supervised learning and the unsupervised learning. BCN has many desirable properties such as flexibility of dynamic structure, high classification accuracy, short learning time, and short recall time. Pitch Detection algorithm is a heuristic model that can solve the difficulties such as scaling invariance, time warping, time-shift invariance, and redundance. This recognition algorithm has shown recognition rates as high as 95% for speaker-dependent as well as multispeaker-dependent tests.

An adaptive EEG waveform detection is presented. The method is based on a layered process model. The model allows the bilateral information exchange across the layers. The criteria for the waveform detection and epoch-wise classification can be adapted according to the higher layer context information embedded in a wider range of adjacent signals. The designed system is experimentally tested to show the adaptive operation of the waveform detection.

This paper proposes a monitoring method using an infrared temperature sensor in laser surface hardening process. To investigate the validity of the method a series of experiments are performed for various conditions. The experimental results show that the surface temperature depends upon the laser power, travelling speed and surface conditions of a specimen. Especially, the laser surface hardening process is greatly influenced by the surface conditions of the specimen, such as coating thickness and materials.

This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

This paper present controller designs based on the configuration control framework for a redundant manipulator to accomplish the basic task of desired, end-effector motion, while utilizing the redundancy to achieve the additional tasks such as joint motion control, obstacle avoidance, singularity avoidance. etc. A task based decentralized adaptive scheme is then applied for the configuration variables to track some reference trajectories as close as possible. Simulation results for a direct-drive three-link arm in the vertical plane demonstrate its capabilities for performing various useful tasks.

An efficient dynamic control algorithm that outperforms existing local torque optimization techniques for redundant manipulators is presented. The method resolves redundancy at the acceleration level. In this method, a systematic switching technique as a trade-off means between local torque optimization and global stability is proposed based on the stability condition proposed by Maciejewski [1]. Comparative simulations on a three-link planar arm show the effectiveness of the proposed method.

The inverse kinematic solutions for redundant manipulators using the optimality augmented resolution schemes have been used without investigating the characteristics of the optimal solutions. The questions with this kind of resolution methods are answered in this paper, that is (i) the characteristics of solutions, (ii) of algorithmic singularities, (iii) their dimensionality, and (iv) the invariance of the characteristics during resolutions. 3-DOF planar redundant robot is analyzed when the inverse kinematic method is applied with the manipulability as an example.

The kinematic resolutions of redundancy is addressed in this paper. The governing equation for quasistatic behavior of compliance governed redundant manipulators is formulated and the repeatable property of the manipulator is proposed. Then the compliance paradigm is used to resolve the redundancy in a repeatable way. The compliance paradigm is one under which the controller simulates the imaginary manipulator which is governed to move by real joint stiffness. The equation is expressed as the weighted pseudoinverse with the configuration dependent weighting matrix. Algorithmic singularities arisen from this scheme are also discussed.

For a multi-input, multi-output system, it is widely known that feedback control gain presents extra freedom pole placement problem. An eigenstructure assignment utilizes this freedom for assignment of all or some elements of the closed-loop eigenvectors. In this paper, a nonlinear optimization technique is adopted to obtain a small gain controller that assigns closed-loop eigenvalues and elements of eigenvectors simultaneously. To illustrate the approach, a numerical example of the Airplane mode decoupling using an advanced fighter is shown.

An efficient method of formulating the equations of motion of multibody systems is presented. The equations of motion for each body are formulated by using Newton-Eulerian approach in their generic form. And then a transformation matrix which relates the global coordinates and relative coordinates is introduced to rewrite the equations of motion in terms of relative coordinates. When appropriate set of kinematic constraints equations in terms of relative coordinates is provided, the resulting differential and algebraic equations are obtained in a suitable form for computer implementation. The system geometry or topology is effectively described by using the path matrix and reference body operator.

Optimal model following control scheme is to design the controller which makes the response of real system follow that of desirable model. This kind of design scheme is developed for first order system. We extends the scheme for second order system regarding the characteristics of mechanical second order system for vibration suppression of flexible structures. The model of mechanical second order system is obtained using suitable damping ratios and natural frequencies. Using this scheme, we can design the good controller which uses the characteristic of second order system. Numerical examples are presented which were used optimal model following control scheme.

This paper extends the authors' prior work on the regulation of flexible space structures via partial feedback linearization (PFL) methods to articulated systems. Recursive relations introduced by Jain and Rodriguez are central to the efficient formulation of models via Poincare's form of Lagrange's equations. Such models provide for easy construction of feedback linearizing control laws. Adaptation is shown to be an effective way of reducing sensitivity to uncertain parameters. An application to a flexible platform with mobile remote manipulator system is highlighted.

This paper presents design criteria of an overlapping decentralized controller by investigating the controllability and closed loop stability of the expanded system. To determine the criteria we classify the overlapping decentralized controller into an overlapping expanded controller and a contractible controller. It is shown that conditions of system expansion to design these controllers are differently used. The overlapping expanded controller needs the aggregation conditions due to the importance of a structure of the expanded system. The contractible controller which intends to use in the original space needs the restriction because of stability of the original system.

A simplified pole-placement design method is developed by analysing dynamic characteristics of the switching dynamics. Unlike the design procedure of conventional pole-placement, in the proposed method, overall state-space is directly decomposed into two invariant subspaces by the projection operator which is defined in the equivalent system, and then the closed-loop poles are assigned to each subspace independently. Hence, computations for state-feedback gain matrix are easy and simple.

We develop a neural network control algorithm for the ACS (Advanced Control System). The ACS is an extended version of the DCS (Distributed Control System) to which functions of fault detection and diagnosis and advanced control algorithms are added such as neural networks, fuzzy logics, and so on. In spite of its usefulness proven by computer simulations, the neural network control algorithm, as far as we know, has no tool which makes it applicable to process control. It is necessary that the neural network controller should be turned into the function code for its application to the ACS. So we develop a general method to implement the neural network control systems for the ACS. By simulations using the simulator for the boiler of 'Seoul fire power plant unit 4', the methodology proposed in this paper is validated to have the applicability to process control.

We developed fault diagnosis fuzzy expert system for ACS(Advanced Control System). ACS is a DCS(Distributed Control System) with advanced control algorithm fault tolerance capabilities, fault diagnosis functions, and so on. Fuzzy expert system developed for an ACS in this paper gives an operator alarm signal depending on the state of process value and manipulated value, and the cause of alarm in real time. Simple experiment result with several rules for the-fault-diagnosis of drum level loop in Seoul-Power-Plant.

In this paper, the GPC algorithm is developed for ACS(advanced control system). ACS equals to DCS(distributed control system) with some advanced control algorithm, for example, fuzzy logic controller, autotuning. By its embedded structural control language, which uses simple function codes corresponding to each function blocks, it is possible to construct multiloop controller. The developed GPC function code is divided by RLS (recursive least square) parameter estimator and GPC controller. Simulation result show the availability of GPC function code using the control language.

This paper is concerned with an automatic generation of BOM (Bill Of Material) for a bicycle frame set using a knowledge based system. The major components module system includes : (1) Part information retrieval in CAD drawing, (2) BOM code generation rule, and (3) Database interface. The knowledge based system includes a rule base and a fact base. The fact base consists of basic, variant, and optional components of the standard BOMs of frame sets. The rule contains rules for generating new BOM code in case that the specified is not in the database. The system was implemented on a SUN workstation under Open Windows environments. AutoCAD for CAD drawing was also used.

In accordance with increase, if electronic power demanded, more efficient supervisory control of distribution system will be required. This study contains development of MMI(man-machine-interface) system with GUI(graphic-user-interface), for the automatic power distribution system. The main function of MMI system is to edit network of power distribution and to management of data base for network. The GUI function of MMI system enables more efficient management of power distribution system.

A fast algorithm based upon geometry to measure the wafer center and the position of a wafer fiducial mark is developed and implemented on a single-axis aligner. Design issues for a controller when a National Semiconductor's LM629 is used as a PID controller of an aligner are discussed. Performance of an aligner with the algorithm and a LM629 was measured in experiments. The result shows that it takes about 4.1 seconds on average to align a hot wafer supported by metal pins on the chuck.

A loop-shaping LQ controller is synthesized for tandem cold mills. And a new loop-shaping technique is suggested for LQ controller design. The suggested loop-shaping LQ control system is compared with the standard loop-shaping LQ control system. The simulation results show that the thickness and interstand tension control accuracy of tandem cold mills can be improved by the compensated loop-shaping LQ controller.

To service with high quality electricity to customer, the utilities consider the DAS (Distribution Automation System) as a good means of it. The backbone of the DAS are communication and computer technique. Most of all, from the economical and functional point of view, the selection of transmission media for system communication is the key factor to achieve a successful DAS. In this paper author propose the method of the DAS communication which share its channel with CATV transmission line and analyze the effect.

In this paper asymptotic formulate for performance characteristics throughput, delay) of large scale token-passing networks with priorities and limited service are given. In particular, adaptive control procedures for obtaining optimal buffer capacity with respect to each priority and optimal limited service are shown. All results obtained are supported by simulations.

In this study, a DNC(Distributed Numerical Control) management system is designed that can directly control and manage hybrid CNC machine tools on real-time. And management software is developed to inter-communicate field informations with CNC controllers using an interface processor(Intelligent Multi Communication Board, IMCB). Especially, IMCB supports that DNC system sends and receives part program with CNC controllers in the form of real-time multi-tasking.

In this paper, the instruction set and the architecture of a RISC processor for programmable logic controller is suggested. From the measurement of existing programs, the characteristics of ladder instructions are analyzed. The instruction set is defined so that the existing ladder program can be reused with simple translation. Because bit instructions controls the behavior of word instructions, the processor suits for high level language like SFC. Simulations show that the PLC with the suggested processor is twenty times faster than the PLC with the multi-purpose microprocessor.

In mechanical structure design area, many FEM (Finite Element Method) packages are used. But the design using FEM packages depends on an iterative trial and error manner and general CAD systems cannot cope with the change of parameters. This paper presents a methodology for building a designing system of a mechanical structure. This system can generate the drawing for a designed structure automatically. It consists of three steps: generation of a structure by selection of the parameters, stress analysis, and generation of a drawing using CAD system. FEM module and parametric CAD module are developed for this system. Inference engine module generates the parameters with a rule base and a model base, and also evaluates the current structure. The parametric design module generates geometric shapes automatically with given dimension. Parametric design is implemented with the artificial intelligent technique. In older to the demonstrate the effectiveness of the developed system, a frame set of bicycle was designed. The system was implemented on an SUN workstation using C language under OpenWindows environment.

In manufacturing press die with free surface, grinding operation is an important post process for surface finish and dimensional accuracy. With the advancement of NC technology. surface grinding operation is increasingly replaced by the gantry type manipulator. As the mechanics for grinding operation is different from machining operation, conventional CAM system for machining operation is hard to apply. In this. paper, we develop a five-axis CAM system by which an efficient gantry trajectory can be planned and verified. The developed system consists of four conceptual modules; namely CAD, PROCESS. CAM, and ANALYSIS. In the CAD module, the machined surface is represented by CL-data or surface modeler, and process parameters are specified by the PROCESS module. Then, the CAM module generates a series of grinding paths based on the grinding mechanics together with process databases for tool spaces and grinding conditions. The generated paths are verified via ANALYSIS module. Validation via real experiments is left for further study.

In this paper, we suggest a new algorithm diminishing the chattering in sliding mode control by setting a dead-band along the switching line on the phase plane although nonlinear terms of an nonlinear system are regarded as disturbances and apply this algorithm to the trajectory control of SCARA robot By this algorithm, we can expect the high performance of the trajectory trajet of an industrial robot which needs a robust and simple algorithm.

The tip of the flexible robot arm has to be controlled by the active control reducing vibration because it has residual vibration after getting to desired position. This paper presents an end-point position control of a 1-link flexible robot arm having tip mass by the PID control algorithm. The system is composed of a flexible arm with tip mass, dc servomotor and ballscrew mechanism under translational motion. The feedback signal composed of the tip displacement measured by laser sensor, estimated velocity and acceleration is used to control the base motion. Theoretical results are obtained by applying the Laplace transform and the numerical inversion method to the governing equations. After the flexible robot arm reaches to. the desired position, the residual vibration is controlled by the PID algorithm. This paper gives the simulation and experimental results of end-point responses according to changing tip-mass and arm length. And this algorithm shows good effects of reducing the residual vibration. Approximately, theoretical response is in good agreement with experimental one.

This paper describes a control scheme for a robot manipulator system which uses visual information to position and orientate the end-effector. In this scheme, the position and orientation of the target workpiece with respect to the base frame of the robot are assumed to be unknown, but the desired relative position and orientation of the end-effector to the target workpiece are given in advance. The control scheme directly integrates visual data into the servoing process without subdividing the process into determination of the position and orientation of the workpiece and inverse kinematics calculation. A neural network system is used for determining the change in joint angles required in order to achieve the desired position and orientation. The proposed system can be control the robot so that it approach the desired position and orientation from arbitrary initial ones. Simulation for the robot manipulator with six degrees of freedom will be done. The validity and the effectiveness of the proposed control scheme will be verified by computer simulations.

A fuzzy controller of a manipulator with artificial rubber muscles is proposed. The fuzzy logic controller as a compensator is described to control the trajectory tracking of a -two link manipulator, where computed torque control method has already assumed to be applied. We shows that the fuzzy compensator with a simple adaptive scaling technique is effective for the robust control when there exist model uncertainties and/or untuned feedback gains. The effectiveness of the proposed control method is illustrated by some experimental results for a circular path tracking.

A scara type Direct Drive Arm(DDA) with two degrees-of-freedom is designed and implemented. The direct drive motor is used to furnish large torque to reduce the modeling error by the gear and chains. To control the DDA, a multiprocessor control structure with multirate dynamic control algorithm is designed. In the control algorithm, the dynamics of system is used to calculate the nominal control torque and the feedback controls are calculated with a parallel processing algorithm for each joint. The laboratory experiments on Hong-Ik DDA by dynamic control algorithm are presented and compared to that of PID control algorithm. This result shows that the proposed controller guarantees small trajectory error and stability. With this research, Hong-Ik DDA is expected to be utilized as A basic tool for robotics and control engineering.

A fuzzy reasoning method is proposed for the implementation of control systems based on non-fuzzy microprocessors. The essence of the proposed method is to search the local active miles instead of the global rule base. Thus the reasoning is conveniently performed on a master cell as a fuzzy accelerating kernel, which is transformed from an active fuzzy cell. The interpolative reasoning is simplified via adopting the algebraic product of fulfillment for the conditional connective AND and the weighted average for the rule sentence connective ALSO.

Fuzzy logic is applied to a roll autopilot for missiles. Fuzzy rules are made so that the response duplicates that of the conventional control law for some flight condition. A scaling factor of the fuzzy controller is then scheduled by the missile velocity and altitude information to cope with the variation of the roll dynamics from that flight condition. By computer simulations and calculation of the stability margin, it is shown that the fuzzy control is robuster than the conventional one over the flight envelope even though two control laws work similarly for some flight conditions.

An algorithm of fuzzy predictive sliding control is proposed to design a jet engine control system. Sliding control using predictive scheme is adopted to compensate the time delay of fuel injector. Fuzzy rule-base is also introduced to adjust the command input for suppressing the surge. The potential of the proposed algorithm is shown through simulations utilizing a typical engine-only model.

To design a fuzzy controller for DC servo-motor, a systematic procedure is proposed. Fuzzy rule base is simply designed through utilizing both the PID gain and the pole-zero cancelation. The results of simulation show that the control system has good performances.

A fuzzy digital controller is combined an autopilot system for compensating the cross coupling effect of the induced roll due to the dynamic characteristic of three fin torpedo. However the utilization of fuzzy chip has many interfacing problems with typical microprocessors of the guidance and control unit. Since a fuzzy digital controller on a microprocessor uses a finite word length A/D converters arul D/A converters, ADC and DAC may generate nonlinear effects such as deadband and limit cycle phenomena. In this paper, the robustness of fuzzy digital controller is tested with ADC a finite word length.

A nonlinear control algorithm for the depth control of underwater vehicles is presented. In order to consider the deadzone effect of the flow control valve, a nonlinear fuzzy logic controller (FLC) is synthesized and combined with a linear proportional-derivative-acceleration (PDA) controller, which is called, the PDA/FLC controller. And, to show the effectiveness of the PDA/FLC control system, it is compared with the linear PDA control system through computer simulation. It is found that the PDA/FLC control scheme is a suitable one to maintain the desirable depth of underwater vehicles with deadzone.

A robust fuzzy self-organizing controller(SOC) is proposed for an environmental temperature chamber. Although fuzzy SOC can improve the performance of nonlinear system, the controller is ineffective to solve the performance degradation owing to the time varying factors. In this paper, we construct the fuzzy SOC with a predictive scheme based on the 386PC. The usefulness of the proposed scheme is shown through the comparison of the PI controller and the fuzzy controller.

A pilot system for flexible automatic assembly has been built at ASRI in Seoul National University. The system is designed for being capable of assembling different variants and products. The system consists of three industrial robots, four free-flow conveyors, automatic tool changers, RCC and fixtures. This paper describes the concept and the technical solutions of the developed flexible assembly cell. Results of performance evaluation using colored petri net are also presented and discuss.

This paper presents linear programming neural networks for job-shop scheduling. The starting times of tasks and constraints are formulated as the linear programming problem. A modified Hopfield neural network is proposed for solving job-shop scheduling.

The real time control system for FMS(Flexible Manufacturing System) is implemented at this paper. To achieve this goal, the Colored and Timed Petri-Net model is constructed and used to simulate the real time operation of FMS. Using the Colored and Timed Petri-Net model, evaluating any kind of FMS plant is possible. On-line shceduler, intelligent dispatcher, real time monitor and the simulation model of shop floor are contructed using LAN communication, relational database system in this paper. Finally, this real time control system is applied to the FMS/CIM center at Seoul National University.

We applied the simulation method using Petri Nets to a FMS model. Generally ordinary Petri Net would be short of describing a real FMS operations. Hence we adopted the extended Petri-Mets(EPN) and timed places in order to have performance evaluation. Our simulator use data based modeled of Petri Nets in simulation. We can enhance the overall production rate of the system with the obtained results over a number of simulations.

In this study, we discuss the design of the expert system for the scheduling of the FMC(Flexible Manufacturing Cell) consisting of the several versatile machines. Due to the NP property, the scheduling problem of several machine FMC is very complex task. Thus we proposed the two heuritstic shceduling algorithms for solving the problem and constituted the algorithm based of solving the problem and constituted the algorithm base of ISS(Intelligent Scheduling System) using them. By the rules in the rule base, the best alternative among various algorithms in algorithm base is selected and applied in controlling the FMC. To show the efficiency of ISS, the scheduling output of ISS and the existent dynamic dispatching rule were tested and compared. The results indicate that the ISS is superior to the existent dynamic dispatching rules in various performance indexes.

The environment for surface mounting machines plays an important role in a throughput. An approach to organize the optimal integrated environment for surface mounting machines is presented to increase a throughput. An optimization problem is divided into a feeder setting problem and a task sequencing problem. Two algorithms for each problem are proposed. The feeder setting problems is optimized by an algorithm based on heuristic methods. The task sequencing problem is modeled as a TSP(Traveling salesman problem). An algorithm based on a heuristic tour-to-tour improvement method for TSP is proposed to optimize the task sequencing problem. A simulation is carried out to test developed algorithms.

In this paper, utilizing the line balancing algorithm proposed to deal with various situations of automated assembly line, the optimal solution can be derived by the branch and bound method of analysis. By the application of line balancing algorithm to telephone assembly line, thoughput is improved by 3.38%. Therefore, in the proposed line, blicking phenomena were reduced and smooth line-flow was achieved, and uniform distribution of utilization rate of each machine is obtained.

For successful implementation of robotic painting system, a structured design and analysis procedure is necessary. In designing robotic system, both functional and economical feasibility should be investigated. As the robotization is complicated task involving implementation details(such as robot selection, accessory design, and spatial layout) together with operation details, a computerized method should be sought. However, any conventional robotic design system and off-line programming system cannot accomodate such a need. In this research, we develop an interactive design support system for robotization of a cycle painting line. With the developed system called SPRPL(Simulation Package for Robotic Painting Line) users can design the painting objects(via FRAME module), select robot model (ROBOT), design the part hanger (FEEDER), and arrange the workcell. After motion programming (MOTION), the design is evaluated in terms of: a) workspace analysis, b) coating thickness analysis, and c) cycle time (ANALYSIS). By iterative design and evaluation procedure, a feasible and efficient robotic design can be attained. As the developed system has motion planning and analysis features, it can be also used as an off-line robot programming system in operation stage. Including the details of each module, this paper also presents a case study made for an actual painting line.

A communication system in an industrial robot controlle is proposed for the implementation of an efficient FA system. Different from existing industrial robot controllers which use binary I/O for the communication with external systems, the robot controllers having the proposed communication system can exchange various information with external systems. Furthermore, the robot motion and the communication with external systems can be performed simultaneously. The structure of hardware and software in the communication system is explained to show how to acheive these two operations simultaneously.

The problem of tension control in metal-strip processing line is discussed. A new mathematical dynamic model which relates tension change, motor-speed change and roll-gap change is developed. Through the computer simulation of this model, parameter sensitivity, the tension transfer phenominon, and static and dynamic characteristics of strip tension were studied. Guidelines are developed to help one selecting locations of the master-speed drive in multi-drive speed control for tension adjustment and reducing the effect of interaction between tension and roll gap control.

This paper introduces a case of SCADA System replacing from centralized processing system to distributed/open architecture system. The cons and pros of the distinctive two system configurations were studied and the requirements of new system that would be enable to easily follow 21 century's technical and operational inovation were presented.

The control-ability of vehicle active suspension is strongly affected by the performance of pressure control valve especially in the view of dynamic response and energy consumption. Important design parameters in the valve are selected and the effect of variation of those is analized experimentally to enhance the performance of pressure control valve used in Active Suspension.

The performances of a vehicle active suspension system with an optimal variable structure controller are compared to those of passive suspension system and active suspension systems with sky-hook and optimal controllers. The quater car model has a 2 DOF which accounts for vertical motions of a sprung and a unsprung masses. The transient responses are analyzed when a vehicle passing through a bump with a constant speed and the frequency responses are analyzed for white noise input at wheel. Particulary, RMS responses are also analyzed. It is shown that the optimal variable structure controller gives better performance of the vehicle active suspensio system than an optimal and a sky-hook controller.

A highly efficient hydropneumatic water supply system type BGY is designed and built in accordance with ISO standard. The technical features of BYG type pump unit can be summarized as follows: - reduce hydropneumatic tank capacity at the ratio of 1/10 - 1/30 compared with conventional method. - ISO standard pumps can be used. - the development of highly efficient water supply system type BYG is based on long-term experiences with the proven constant pressure water supply technique which minimize pressure fluctuation, rapid pilsation, etc. The text contains the operation principle of BYG type water supply system, introduction of closed cycle control process focused on Mini PC and experimental results of type BYG-IVS-90x45.

Dynamic characteristics of a hydraulic power supply are studied theoretically and computationally. The transfer function between the supply pressure and the load flow is derived considering relief valve dynamics, accumulator dynamics, and flow line dynamics. Frequency responses and time responses are obtained in many conditions using the transfer function and nonlinear mathematical model respectively.

Variable-displacement pumps are inherently more efficeint than fixed-displacement pumps under varying loads. Their energy-saving characteristics can be improved by the use of special control. This paper shows the improvement of the system by the use of load-sesing technique.

The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment a noble FLC is proposed, which is based on simple control rules while offering easy tuning of control parameters by utilizing real operation characteristics of an operator. The proposed FLC consists of two parts, the proportional controller part and the FLC part. Experiments are carried out on a test bed which is built around a commercial excavator. The controller is applied to bhe leveling of excavator's bucket tip, which is one of the main functions in an excavator's operation.

For the HST(Hydrostatic Transmission) consisted of a variable displacement axial piston pump and motor, a speed controller with efficiencies considered is proposed. To consider a efficiency in speed control, the displacements of pump and motor which maximize a steady state efficiencies with a various load torque are calculated through computer simulation and these results are reflected to speed controller which has PI control structure with cross over control scheme. It is shown through computer simulation that the proposed controller gives better steady state efficiencies compared with the conventional controller and good transient responses.

Active roll control can improve handling and ride comfort. Dynamic characteristics of the hydraulic actuators for active suspension, which can be modeled as the 1'st order time lag system, hinders the performance improvement. To overcome this shortcoming a predictive controller is designed based on 3 d.o.f. linear vehicle handling model. The effect of this controller is studied through the simulation based on 10 d.o.f. nonlinear vehicle model and the results is compared to that of feedforward controller which uses lateral acceleration as control signal.

It has been well known that the assumption of full state availability is one of the most important restrictions to the practical realization of VSCS. And several attempts to alleviate the assumption had been made. However, it is not easy to find a positive scheme among them. Recently, an output feedback variable structure control system(OFVSCS) was proposed and the effectiveness of the scheme was validated for the disturbance free systems. The purpose of this study is to propose a robust OFVSCS that have the robust properties against process parameter variations and external distrubances by extending the basic OFVSCS and to evaluate its control performances through power system stabilizer design example. The ROFVSCS is composed of dynamic switching function and output feedback switching control inputs that are constructed by the use of the unknown vector modeling technique. With the proposed scheme, existence of sliding mode is guaranteed and any nonzero bias can be suppressed in the face of disturbances and process parameter variations as far as well-known matching condition is satisfied. Due to the fact that the ROFVSCS is driven by small number of measured informations, the practical application of VSCS for the systems with unmeasurable states and for high order systems that conventional schemes cannot be applied, is possible with the proposed scheme. It is noticeable that the implementation cost of VSCS can be considerably reduced without sacrifice of control performances by adopting ROFVSCS since there is no need measure the states with high measurement cost.

In this paper, an variable structure system with an integral-augmented sliding surface is designed for the improved robust control of a uncertain multi-input multi-output(MIMO) system subject to the persistent disturbances. To effectively remove the reaching phase problems, the integral augmented sliding surface is defined, then for its design, the eigenstructure assignment technique is introduced. To guarantee the designed performance againts the persistent disturbance, the stabilizing control for multi-input system is also designed. The stability of the global system and performance robustness are investigated. The example will be given for showing the usefulness of algorithm.

Variable structure control is applied to the robust output tracking control problem of general nonlinear multi-input multi-output (MIMO) systems. Using the concept of relative degree and minimum phase, input/output(I/O) linearization is undertaken. For I/O the linearized system, a new sliding hyperplanes design method is proposed. In this procedure, we can construct very robust and efficient sliding mode controller for general nonlinear systems of relative degree higher than two. The control results are illustrated by adopting a numerical example.

A buck-boost zero current switched(ZCS) series resonant AC to DC converter for the DC output voltage regulation together with high power factor is proposed. The proposed single phase AC to DC converter enables a zero current switching operation of all the power devices allowing the circuit to operate at high swtiching frequencies and high power levels. A dynamic model for this Ac to DC converter is developed and an analysis for the internal operational characteristics is explored. Based on this analysis, a switched discrete sliding mode control(SDSMC) technique is investigated and its advantages over the other types of current control techniques are discussed. With the proposed control technique, the unity power factor without a current overshoot and a wide range of output voltage can be obtained.

In this paper we present the differential geometric approach for the analysis and design of sliding modes in nonlinear variable structure feedback systems. We also design the robust controller for the nonlinear system using variable structure control theory on the basis of differential geometric methods and feedback linearization applying Min-Max control based on the Lyapunov second method. The robustness against parameter uncertainties for robot manipulators with flexible joint is considered. Simulation results are presented and show the advantage of the proposed nonlinear control method.

We study how to design conventional feedback controllers to drive chaotic trajectories of the well-known systems to their equilibrium points or any of their inherent periodic orbits. The well-known chaotic systems are Heon map and Duffing's equation, which are used as illustrative examples. The proposed feedback controller forces the chaotic trajectory to the stable manifold as OGY method does. Simulation results are presented to show the effectiveness of the proposed design method.