We propose a VSC(Variable Structure Controller) with a PI-type reaching law. In General, conventional VSCs with a reaching law including a discontinuous term have the chattering problem, and thus the system may be unstable due to the disregarded high frequency dynamics in the modeling process. To resolve this problem, the PI-type reaching law is proposed in this paper. The proposed reaching law makes it easy to determine the reaching dynamics as well as the reaching time by utilizing the 2nd-order system analysis. Furthermore, since the discontinous term is not involved in the reaching law, the chattering is considerably reduced. To show the effectiveness of the proposed scheme, the stability of the proposed system is proved by Lyapunov method and the computer simulations are performed for the Ball Balance System.

지구를 원궤도로 돌고 있는 위성 운동과 지진에 흔들리는 건물 진동을 선형 확률적 미분 방정식으로 나타내고 최적화 제어를 위하여 리스크 센서티브 제어기를 사용한다. 리스크 센서티브 파라미터에 따라서 코스트 함수의 평균과 분산이 변하게 된다. 이 파라미터가 무한히 커지면 리스크 센서티브 제어기는 기존의 LQG 제어기와 같아지므로 리스크 샌서티브 제어이론은 LQG 제어 이론을 포함한 종합적인 이론이다. 이 논문에서는 리스크 센서티브 이론을 소개하고, 리스크 센서티브 제어 방식의 성능 측정및 평가 방법을 도출하기 위하여 공분산을 이용하면 리스크 센서티브 제어기는 기존의 LQG 제어기 보다 우수한 성능을 나타낸다는 것을 보여준다. 시뮬레이션을 통하여 위성의 자세및 궤도 운동 제어와 건물 진동 제어에 활용된 리스크 센서티브 제어기의 향상된 성능과 안정성을 보여준다.

Autonomous Underwater Vehicles(AUVs) have become an important tool for various purposes in subsea: inspection, recovery, construction, etc., and the development of autonomous control system is luglay desirable- thete zffe many problems associated with designing the control system for AUV due to unknown underwater envimn-Tnent, the possibility of subsystem failures, and unpredictable changes in the dynamics of the vehicle. In this paper, an autonomous control system based on the intelligent control theory to enhance operation efficiency of the ALTV is presented. The control system has a hierarchical structure which consists of mission planning level, mission control level, navigation level, and execution level. The performance of the control system is investigated by computer simulation. The results show that the proposed control system can be applied successfully to the AUV in spite of the possibility of failures in the vehicle and the collision hazard in the sea environment.

A new transfer alignment algorithm using the velocity and the quaternion partial matching methods is proposed to reduce the effect of a ship's Y-axis flexure on the performance of azimuth error estimation of Kalman filter. The simulation results show that it can significantly reduce the effect of Y-axis flexure on error estimation by the transfer alignment algorithm. As its results, azimuth transfer alignment error is reached up to 3 mrad under proper roll and pitch attitude motion of the ship.

In this paper, we propose a fault diagnosis algorithm to detect and isolate multiple faults in a system. The proposed fault diagnosis algorithm is based on a multiple fault classifier which consists of two ART2 NN(adaptive resonance theory2 neural network) modules and the algorithm is composed of three main parts - parameter estimation, fault detection and isolation. When a change in the system occurs, estimated parameters go through a transition zone in which residuals between the system output and the estimated output cross the threshold, and in this zone, estimated parameters are transferred to the multiple faults classifier for fault isolation. From the computer simulation results, it is verified that when the proposed diagnosis algorithm is performed successfully, it detects and isolates faults in the position control system of a DC motor.

This paper presents neural networks for hybrid position/force control which is a type of position and force control for robot manipulators. The performance of conventional hybrid position/force control is excellent in the case of the exactly-known dynamic model of the robot, but degrades seriously as the uncertainty of the model increases. Hence, the neural network control scheme is presented here to overcome such shortcoming. The introduced neural term is designed to learn the uncertainty of the robot, and to control the robot through uncertainty compensation. Further more, the learning rule of the neural network is derived and is shown to be effective in the sense that it requires neither desired output of the network nor error back propagation through the plant. The proposed scheme is verified through the simulation of hybrid position/force control of a 6-dof robot manipulator.

널리 쓰이는 진화 알고리즘은 크게 두가지가 있다. 유전 알고리즘과 진화 기법이 그것이다. 이들 알고리즘은 실행 전에 사용자가 정해주어야 하는 변수들을 가지고 있다. 본 논문에서는 이 두 알고리즘을 일반화시키고 집단의 크기, 교차변이 연산자 적용 확률 그리고 돌연변이 연산자 적용 확률과 같은 변수들을 알고리즘이 수행되는 동안 스스로 정하는 일반화된 자기 형성 진화 알고리즘을 제안한다. 제안된 알고리즘의 타당성과 효용성은 시스템 동정화와 다개체 시스템 제어의 두가지 복잡한 제어 문제에 대한 적용을 통해 보여진다.

A fuzzy logic controller (FLC) has been widely used for many applications in recent years. But the relationship between control performance and design parameters has not been handled explicity in the conventional theory of fuzzy logic control. In this paper, based on the similarity between an FLC and a variable structure control (VSC) theory, a performance evaluation of an FLC, which gives quantitative accounts on the relationship is presented. The validity of the analysis is verified through extensive computer simulations.

In this paper, a fuzzy generalized predictive control (FGPC) for non-linear plants is proposed. In the proposed method, the receding horizon control is applied to the control part, while fuzzy systems are used for the predictor part. It is suggested that the fuzzy predictor is time-varying affine with respect to input variables for easy computation of control inputs. Since the receding horizon control can be obtained only with a predictor instead of a plant model, the fuzzy predictor is obtained directly from input-output data without identifying a plant model. A parameter estimation algorithm is used for identifying the fuzzy predictor. The control inputs of the FGPC are computed by minimizing a receding horizon cost function with predicted plant outputs. The proposed controller has a similar architecture to the generalized predictive control (GPC) except for the predictor synthesis method, and thus may possess inherent good properties of the GPC. Computer simulations show that the performance of the FGPC is satisfactory.

In this paper, we will show that the torque ripple in closed-loop drives of permanent magnet stepping motors is reduced as properly selected lead angle control method. We propose an instantaneous torque equation, which is the function of lead angle, to estimate the influence on torque ripple. We design a closed-loop lead angle control system based on the proposed instantaneous torque equation and measure the instantaneous torque in various excitation modes. It is shown that torque ripple is greatly reduced, as seen from the experimental results as well as from the computer simulation results. For example, torque ripple reduced from 78.25% to 46.82% in the case of 50 PPS single-phase excitation mode operation.

In this paper, a method has been proposed for error measurement/diagnosis of CNC machine tools using the ball link bar on three dimensional space. For the circular motion error measurement, deviation between the desired and actual test path has been measured and analysed using a new type of ball link which incorporates ideal three point contact between reference balls and sockets. Computer program for the error evaluation has been developed and implemented under PC environment. Using the developed program, the circular test data on a CNC machine tool have been analysed, and thus, machine tool errors were effectively evaluated.

In stereo vision, camera modeling is very important because the accuracy of the three dimensional locations depends considerably on it. In the existing stereo camera models, two camera planes are located in the same plane or on the optical axis. These camera models cannot be used in the active vision system where it is necessary to obtain two stereo images simultaneously. In this paper, we propose four kinds of stereo camera models for active stereo vision system where focal lengths of the two cameras are different and each camera is able to rotate independently. A single closed form solution is obtained for all models. The influence of the stereo camera model to the field of view, occlusion, and search area used for matching is shown in this paper. And errors due to inaccurate focal length are analyzed and simulation results are shown. It is expected that the three dimensional locations of objects are determined in real time by applying proposed stereo camera models to the active stereo vision system, such as a mobile robot.

In this paper, a fuzzy set based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy logic is emoloyed to express the degree of appropriateness when alternative machines are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

DTG(dynamically tuned gyroscope) is a sensor detecting disturbance in angle velocity control loop of EOTS(electro optical tracking system), which is used for the stabilization of gimbal. DTG is classified into rate mode or rate integrated mode according to operating mode. In this paper, basic principles and characteristics of DTG, depending on to operating mode, are compared and the model of rate integrated mode DTG is proposed. Also, the validity of the presented model is verified by computer simulations and experiments.

A prototype of combustion zone monitoring system as been developed and installed into tuyeres of the blast furnace. The system consists of CCD(charge coupled device) cameras, sonic flow meters, an image processor and a personal computer. The personal computer collects raceway luminance data and operational data from the image processor that is connected to the color CCD camera from the blast furnace process computer, respectively. In addition, the sonic flow meters supply coal injection rate data to the personal computer. Then, the personal computer evaluates the combustion conditions with the raceway inspection algorithm. This integrated monitoring system allows us to detect abnormal raceway conditions and the clogging status of coal injection pipe. The image processing techniques of the system enable us to effectively monitor unburnt coal sticking to tuyere tip and injection lance wear conditions. Such a developed system ensures rapid and precise raceway inspection. The image processing capability of the system has helped operator to early detect both the unburnt coal sticking problem and the errosion problem of injection lance. Furthermore, the system could control the abnormal raceway condition based the the analysis results obtained from combustion monitoring.

A new probing mechanism and an active compliance control algorithm have been developed for the in-circuit test of a PCB( printed circuit board ). Commercially available robotic probing devices are incapable of controlling contact force generated through rigid probe contacts with a solder joint, at high speed. The uncontrollable excessive contact force often brungs about some defects on the surface of the solder joint, which is plastically deformable over some limited contact force. This force also makes unstable contact motions resulting in unreliable test data. To overcome these problems, we propose that a serially connected macro and micro device with active compliance provide the best potential for a safe and reliable in-circuit test. This paper describes the design characteristics, modeling and control scheme of the newly proposed device. The experimental results clearly show the effectiveness of the proposed system.