This paper presents a dynamical anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. By regarding the difference of controller states in the absence and presence of saturating actuators as an objective function, the dynamical compensator which minimizes the objective function is derived in an integrated fashion. The proposed dynamical compensator is a closed form of plant and controller parameters. The resulting dynamics of compensated controller reflects the linear closed-loop system. The proposed method guarantees total stability of the resulting system. The effectiveness of the proposed method is illustrated by applying it to a servo motor control system. The paper is an extension of the results in Park and Choi[1].

This paper presents an $H_{\infty)$ output feedback controller design method for linear systems with delayed state, delayed control input, and delayed masurement output. Using a Lyapunov functional, the stability for delayed systems is discussed independently of delays. Also, sufficient condition for the existence of $H_{\infty)$ controllers of any order is given in terms of three linear matrix inequalities(LMIs). Based on positive definite solutions of their LMIs, we briefly explain the way to construct $H_{\infty)$ controller, which stabilizes time-delay systems independently of delays and guarantees an $H_{\infty)$norm bound.

This paper provides some properties of positive real systems in time domain. It is well-known that a positive real system and a bounded real system are closely related by bilinear transform in a frequency domain. By using supply rate and storage function, we show that a positive real system can be transformed into a bounded real system, and that a positive real system can be transformed into another positive real system with in a time domain. Also, we show that an ESPR(extended strictly positive real) system can be decomposed into a feedback system of lossless positive real system and another ESPR system. These results may be used to design an output feedback controller for mixed H$H_2$ESPR problem.

In this paper, we design an optimal model following ${\mu}-$synthesis control system for fuel-injection of diesel engine which has robust performance and satisfactory command tracking performance in spite of uncertainties of the system. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithm with reference model to the optimal determination of the weighting functions that are given by the D-K iteration method which can design ${\mu}-$synthesis controller in the state space. These weighting functions are optimized simultaneously in the search domain which guarantees the robust performance of the system. The ${\mu}-$synthesis control system for fuel-injection designed by the above method has not only the robust performance but also a better command tracking performance than those of the ${\mu}-$synthesis control system designed by trial-and-error method. The effectiveness of this ${\mu}-$synthesis control system for fuel-injection is verified by computer simulation.

In this paper, a unified solution of Hankel norm approximation problem is proposed by $\delta$-operator. To derive the main result, all-pass property is derived from the inner and co-inner property in the $\delta$-domain. The solution of all-pass becomes an optimal Hankel norm approximation problem in .delta.-domain through LLFT(Low Linear Fractional Transformation) inserting feedback term $\phi(\gamma)$, which is a free design parameter, to hold the error bound desired against the variance between the original model and the solution of Hankel norm approximation problem. The proposed solution does not only cover continuous and discrete ones depending on sampling interval but also plays a key role in robust control and model reduction problem. The verification of the proposed solution is exemplified via simulation for the zero-order Hankel norm approximation problem and the model reduction problem applied to a 16th order MIMO system.

In this paper, a robust.adaptive learning control scheme is presented for precise trajectory tracking of rigid mobile robots. In the proposed controller, a set of desired trajectories is defined and used in constructing the control input and learning rules which constitute the main part of the proposed controller. Stable operating characteristics such as precise trajectory tracking, parameter estimation, disturbance suppression, etc., are shown thorugh experiments and computer simulations.

This paper proposes an advanced visual tracking algorithm for the stable grasping of a moving target(2D). This algorithm is programmed to find grasping points of an unknown polygonal object and execute visual tracking. The Kalman Filter(KF) algorithm based on the SVD(Singular Value Decomposition) is applied to the visual tracking system for the tracking of a moving object. The KF based on the SVD improves the accuracy of the tracking and the robustness in the estimation of state variables and noise statistics. In addition, it does not have the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. In the grasping system, a parameterized family is constructcd, and through the family, the grasping system finds the stable grasping points of an unknown object through the geometric properties of the parameterized family. In the previous studies, many researchers have been studied on only 'How to track a moving target'. This paper concern not only on 'how to track' but also 'how to grasp' and apply the grasping theory to a visual tracking system.

This paper describes a hardware implementation method of a Petri Net-based controller. A flexible and systematic implementation method, based on look-up tables, is suggested, which enables to build high speed Petri net-based controllers. The suggested method overcomes the inherent speed limit that arises from the microprocessors by using of matrix-based look-up tables. Based on the matrix framework, this paper suggests various specific data path structures as well as a basic data path structure, accompanied by evolution algorithms, for sub-class Petri nets. A new sub-class Petri net, named Biarced Petri Net, resolves memory explosion problem that usually comes with matrix-based look-up tables. The suggested matrix-based method based on the Biarced Petri net has as good efficiency and expendability as the list-based methods. This paper shows the usefulness of the suggested method, evaluating the size of the look-up tables and introducing an architecture of the signal processing unit of a programmable controller. The suggested implementation method is supported by an automatic design support program.

This paper presents an adaptive fuzzy controller using an neural network and adaptation algorithm. Reference-model following neuro-fuzzy controller(RMFNFC) is invesgated in order to overcome the difficulty of rule selecting and defects of the membership function in the general fuzzy logic controller(FLC). RMFNFC is developed to tune various parameter of the fuzzy controller which is used for the discrete nonlinear system control. RMFNFC is trained with the identification information and control closed loop error. A closed loop error is used for design criteria of a fuzzy controller which characterizes and quantize the control performance required in the overall control system. A control system is trained up the controller with the variation of the system obtained from the identifier and closed loop error. Numerical examples are presented to control of the discrete nonlinear system. Simulation results show the effectiveness of the proposed controller.

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

This paper presents a practical application of fuzzy logic control to temperature control of glass melting furnace. Due to the characteristics of glass melting furnace, a hybrid algorithm of conventional PI controller and fuzzy logic controller is proposed and discussed. Practical implementation results of the production furnace showed the effectiveness of the proposed control algorithm.

In GPS (Global Positioning System) positioning, various measures can be used to select satellites or to evaluate the positioning results. Among these, GDOP (Geometric Dilution of Precision) and RGDOP (Relative GDOP) are the most frequently used. Although these measures are frequently used, the relationship between them is not clearly known. Moreover, the condition number is used as a traditional measure of numerical stability in solving linear equations. Sometimes, the volume of a tetrahedon made by the line of sight vector is used for simplicity. All of these measures share some common properties as well as differences. The relationships between these measures are analyzed in this paper.

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the conveyor speed into consideration. This paper presents an effective method to identify the dynamic tracking line in a robotic workcell. The maximum line speed of a robot is derived in an analytic form using the parameterized dynamics and kinematics of the manipulator, and some of its properties are established mathematically. The identification problem of the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by using a simple numerical technique. Finally, numerical examples are presented to demonstrate the methodology and its applications in workspace specification.

This paper presents the fuzzy optimization model based scheduling methodology for the efficient production control of a FFS(FIexible Flow Shop) under the uncertain production environment. To develop the methodology, a fuzzy optimization technique is introduced in which the uncertain production capacity caused by the random events like the machine breakdowns or the absence of workers is modeled by fuzzy number. Since the problem is NP hard, the goal of this study is to obtain the near optimal but practical schedule in an efficient way. Thus, Lagrangian relaxation method is used to decompose the problem into a set of subproblems which are easier to solve than the original one. Also, to construct the feasible schedule, a heuristic algorithm was proposed. To evaluate the performance of the proposed method, computational experiments, based on the real factory data, are performed. Then, the results are compared with those of the other methods, the deterministic one and the existing one used in the factory, in the various performance indices. The comparison results demonstrate that the proposed method is more effective than the other methods.

This paper presents a novel method for real-time malfunction detection of plasma etching process using EPD signal traces. First, many reference EPD signal traces are collected using monochromator and data acquisition system in normal etching processes. Critical points are defined by applying differentiation and zero-crossing method to the collected reference signal traces. Critical parameters such as intensity, slope, time, peak, overshoot, etc., determined by critical points, and frame attributes transformed signal-to symbol of reference signal traces are saved. Also, UCL(Upper Control Limit) and LCL(Lower Control Limit) are obtained by mean and standard deviation of critical parameters. Then, test EPD signal traces are collected in the actual processes, and frame attributes and critical parameters are obtained using the above mentioned method. Process malfunctions are detected in real-time by applying SPC(Statistical Process Control) method to critical parameters. the Real-time malfunction detection method presented in this paper was applied to actual processes and the results indicated that it was proved to be able to supplement disadvantages of existing quality control check inspecting or testing random-selected devices and detect process malfunctions correctly in real-time.

Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

This paper proposes a fault detection and recovery mechanism for a fault-tolerant Mini-MAP system, and provides detailed techniques for its implementation. This paper considers the fault-tolerant Mini-MAP system which has dual layer structure from the LLC sublayer down to the physical layer to cope with the faults of those layers. For a good fault detection, a redundant and hierarchical fault supervision architecture is proposed and its implementation technique for a stable detection operation is provided. Information for the fault location is provided from data reported with a fault detection and obtained by an additional network diagnosis. The faults are recovered by the stand-by sparing method applied for a dual network composed of two equivalent networks. A network switch mechanism is proposed to achieve a reliable and stable network function. A fault-tolerant Mini-MAP system is implemented by applying the proposed fault detection and recovery mechanism.

철강석 또는 석탄의 적치장에서는 이들 원석을 퍼내어 용광로로 보내주는 불출기(reclaimer)가 사용되고 있다. 불출기를 자동화하려면 야적파일에 불출용 회전 버킷(bucket)을 자동착지시키는 방법이 요구된다. 본 논문에서는 야적 파일 표면위의 버킷 착지점을 추출하는 방법을 제시한다. 이 방법은 파일의 3차원 형상 검출, 파일의 등고선 추출, 불출기의 역기구학해의 도출 및 착지점 추출 알고리즘으로 이루어진다. 파일의 3차원 형상과 거리를 측정하기 위한 3차원 형상 검출기가 2차원 레이저 검출기에 수평주사(scanning)용 모터를 부착하여 개발하였고, 다 단계의 영상처리를 통해 버킷이 작업할 수 있도록 파일의 작업 등고선을 추출하였다. 불출기가 회전 버킷에 의해 기구학적으로 여유자유도로 이루어 졌음을 보였으며, 역기구학 해를 구하는 방법을 아울러 제시하였다. 그리고 버킷의 착지점을 과부하 방지와 단위 시간당 생산성을 최대화하는 성능기준에 근거하여 구하였다. 또한 개발된 시스템을 제철소 원석 야적장의 불출기에 설치 시험하여 타당성을 입증하였다.