제어로봇시스템학회:학술대회논문집
Institute of Control, Robotics and Systems (ICROS)
 기타
Domain
 Machinery ＞ Robot/Automated Machinery
1996.10

This paper addresses the control problem of a mobile robot supporting a task robot with needs to be positioned precisely. The main difficulty residing in the precise control of a mobile robot supporting a task robot is providing an accurate and stable base for the task robot. That is, the endplate of the mobile robot which is the base of the task robot can not be positioned accurately without external position sensors. This difficulty is resolved in this paper through the vision information obtained from the camera attached at the end of a task robot. First of all, the camera parameters were measured by using the images of a fixed object captured by the camera. The measured parameters include the rotation, the position, the scale factor, and the focal length of the camera. These parameters could be measured by using the features of each vertex point for a hexagonal object and by using the pinhole model of a camera. Using the measured pose(position and orientation) of the camera and the given kinematics of the task robot, we calculate a pose of the endplate of the mobile robot, which is used for the precise control of the mobile robot. Experimental results for the pose estimations are shown.

This keynote presentation covers the subject of intelligent systems development for monitoring and control in various NASA space applications. Similar intelligent systems technology also has applications in terrestrial commercial applications. Discussion will be given of the general approach of intelligent systems and description given of intelligent systems under prototype development for possible use in Space Shuttle Upgrade, in the Experimental Crew Return. Vehicle, and in freeflying space robotic cameras to provide autonomy to these spacecraft with flexible human intervention, if desired or needed. Development of intelligent system monitoring and control for regenerative life support subsystems such as NASA's human rated BioPLEX test facility is also described. A video showing two recent world's firsts in realtime visionguided robotic arm and hand grasping of tumbling and translating complex shaped objects in microgravity will also be shown.

In impedance control for contact force tracking it is well known that the reference trajectory of the robot is calculated from known environment stiffness. The accuracy of estimating the environment stiffness determines the performance of the resulting force tracking. Here we present a simple technique, called the trajectory modification technique(TMT), of determining the reference trajectory under the condition that the environment stiffness is unknown. Computer simulation studies have shown that force tracking using the proposed technique is excellent for unknown environment with time varying stiffness.

In this paper, a new shape control law is derived as a result of introducing the parametric curve representation. This control alw is based on the estimation of the curve parameters corresponding to the target joint positions and the target tip position. Estimating target curve parameters makes it possible to find, easily, a simple shape control law by the Lyapunov design method.

Based on the technical innovation of the recent communication system technologies, systems are linked by the worldwide network. We introduce some examples of the multimedia network systems. Especially, we introduce our recent attempt to realize the multimedia telesurgery system using high speed optical fiber network. At first, we shows the technical problems of the multimedia telesurgery. We applied this idea to the intravascular neurosurgery. System configuration for the prototype experiments and experimental results are shown.

In this paper, a sliding mode control scheme that guarantees the smoothness of the control signal and the exponential error convergence is proposed for robot manipulators. The proposed method inserts a low pass filter (LPF) in front of the plant, and the virtual controller is designed for the virtual plant  the combination of the LPF and the robot manipulator. The virtual control signal contains high frequency components because of a switching function. The real control signal, however, always shows a smooth curve since it is an output of the LPF. In addition to the smoothness of the control signal is always assured, the overall system is in the sliding mode at all times, that is, its performance is always invariant under the existence of parameter uncertainties and external disturbances. The closedloop system is shown to be globally exponentially stable.

An experimental research is a useful approach for realizing autonomous mobile robots to work in real environment. We are developing an autonomous mobile robot platform named "Yamabico" as a tool for experimental real world robotics research. The architecture of Yamabico is based on the concept of centralized decision making and functionally modularization. Yamabico robot has two level structure with behavior and function levels, and its hardware and software are functionally distributed for providing incremental development and good maintenancibility. We are using many Yamabico robots in our laboratory to realize the robust navigation technology for autonomous robots. The methodology for experimental and taskoriented approach of mobile robotics will be presented. And some experimental results of real world navigation in indoor and outdoor environment will be shown. be shown.

This paper reviews some of the most prominent and promising areas of chemical process control both in relations to batch and continuous processes. These areas include the modeling, optimization, control and monitoring of chemical processes and entire plants. Most of these areas explicitly utilize a model of the process. For this purpose the types of models used are examined in some detail. These types of models are categorized in knowledgedriven and datadriven classes. In the areas of modeling and optimization, attention is paid to batch reactors using the Tendency Modeling approach. These Tendency models consist of data and knowledgedriven components and are often called Gray or Hybrid models. In the case of continuous processes, emphasis is placed in the closedloop identification of a state space model and their use in Model Predictive Control nonlinear processes, such as the Fluidized Catalytic Cracking process. The effective monitoring of multivariate process is examined through the use of statistical charts obtained by the use of Principal Component Analysis (PMC). Static and dynamic charts account for the cross and autocorrelation of the substantial number of variables measured online. Centralized and decentralized chart also aim in isolating the source of process disturbances so that they can be eliminated. Even though significant progress has been made during the last decade, the challenges for the next ten years are substantial. Present progress is strongly influenced by the economical benefits industry is deriving from the use of these advanced techniques. Future progress will be further catalyzed from the harmonious collaboration of University and Industrial researchers.

A full automatic interpretation of awake electroencephalogram (EEG) had been developed by the authors and presented at the past KACCs in series. The automatic EEG interpretation consists of four main parts: quantitative EEG interpretation, EEG report making, preprocessing of EEG data and adaptable EEG interpretation. The automatic EEG interpretation reveals essentially the same findings as the electroencephalographer's (EEG's), and then would be applicable in clinical use as an assistant tool for EEGer. The method had been developed through collaboration works between the engineering field (Saga University) and the medical field (Kyoto University). This work can be understood as an artificial realization of human expert skill. The procedure for the artificial realization was summarized in a methodology for artificial realization of human skill which will be applicable in other fields of systems control.

This paper deals with the flexible manipulator with rotational and translational degrees of freedom, which has an arm of timevarying length with the prismatic joint. The tracking control problem of the flexible manipulator is considered. First we design the controller of the 2type robust servo system based on the finite horizon optimal control theory for the trajectory planned as a discontinuous velocity. Next, to reduce the tracking error, we use the method of the dynamic programming and of modifying the reference trajectory in time coordinate. The simulation results show that the dynamic modeling is adequate and that the asymptotic stabilization of the flexible manipulator is preserved in spite of nonlinear terms. The PTP control error has been reduced to zero completely, and the trajectory tracking errors are reduced sufficiently by the proposed control method.

The development of future aircraft that involves the expanded flight envelop will place increased performance requirements on the design of the flight control system. Maneuvering areas are expanding into flight envelopes characterized by significantly larger levels of modeling uncertainty than encountered in present flight control designs. Conventional flight control techniques that ignore the effects of large parameter variations, modeling uncertainties and nonlinearities, will likely produce designs with poor performance and robustness. Recent advances in modern control theories called advanced control theories, most notably the H
$\_$ .inf./ synthesis technique, adaptive control and neural network application, offer the promise of a design technique that can produce both high performance and robust controllers for next generation aircraft. This special lecture will survey the recent development in advanced flight control and review the possible application of advanced control theories. 
This paper is a study on the fuzzy force control of a miniature gripper driven by piezoelectric bimorph actuator. The system is composed of two flexible cantilevers, a stepping motor, a laser displacement transducer and two semiconductor force sensors attached to the beams. Obtained results show that the present artificial finger system works well as a miniature gripper, which produces approximately 0.06N force in the maximum. Further, the fuzzy position/force control algorithm is applied to the softhanding gripper for stable grasping of a object. It revealed that the fuzzy rulebased controller be efficient controller for the stable drive of the flexible miniature gripper. It also showed that two semiconductor strain gauges located in the flexible beam play an important roles for force control, position control and vibration suppression control.

Recently, AC variablespeed motors are used for many steel rolling mill drive systems, because of their low maintenance and enhanced control performance. We have been applied GTO inverters for these AC motor drive systems since 1993. We have developed world largest 6inch diameter GTO and large capacity 3level GTO inverter up to 20000(kVA). As an example, in this paper, we describe the main circuit, system arrangement and control features of the 6inches GTO inverters to drive rougher mills for hot strip mill of Pohang Iron & Steel Co., Ltd. The motor capacity is 6000(kW), and it's overload is 250(%).

A bag is a setlike entity which can contain repeated elements. Fuzzy bags have been studied by Yager, who defined their basic relations and operations. However, his definitions of the basic relations and operations are inconsistent with the corresponding relations and operations for ordinary fuzzy sets. The present paper presents new basic relations and operations of fuzzy bags using a grade sequence for each element of the universal set. Moreover the .alpha.cut, tnorms, the extension principle, and the composition of fuzzy bag relations are described.

Traffic signal cycle optimization is one of the most efficient ways for reducing fuel consumption and improving vehicle waiting time of highsaturated traffic conditions. But most research focused on lowsaturated traffic conditions. Only a few studies have researched traffic control for highsaturated traffic conditions. In this paper reviews the problem of conventional traffic signal system and creates optimal traffic cycle of at the bottom traffic intersection using 27 fuzzy rules. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

This paper proposes identification and control algorithm of nonlinear systems and the proposed fuzzyneural network has following characteristics. The network is roughly divided into premise and consequence. The consequence function is nonlinear function which consists of three parameters and the membership function in the premise contains of two parameters. The parameters in premise and consequence are learned by the extended backpropagation algorithm which has a modified form of the generalized delta rule. Simulation results on the identification show that this method is more effective than that of Narendra [3]. The indirect fuzzyneural control is made of the fuzzyneural identification and controller. Result on the indirect fuzzyneural control shows that the proposed fuzzyneural network can be efficiently applied to nonlinear systems.

To design high quality products at low cost is one of very important task for engineers Design optimization for performances can be one solution in this task. This is robust design which has been proved effectively in many field of engineering design. In this paper, the concept of robust design is introduced and combined to fuzzy optimization and nonsingleton fuzzy logic system. The optimum parameter set points were obtained by the fuzzy optimization method and nonsingleton fuzzy logic system. These methods are applied to a filter circuit, a part of the audio circuit of mobile radio transceiver. The results are compared each other.

An optimal preview controller based on the discretetime
$H_{.inf}$ control is presented. The preview controller is synthesized by considering the bounded unknwon disturbances as well as previewable commands and disturbances. The controller derivation procedure is analogous to the LQbased scheme. The designed preview gain matrix has a similar structure as the LQbased one. As the infinity norm .gamma. of the transfer function matrix tends to .inf., the preview gains obtained by$H_{\infty}$ control method approach to the gains by the LQR. The LQbased preview gains are verified to be subsets of the$H_{.inf}$ based preview gains.. 
This note considers the
$H^{\infty}$ controller design problem for linear systems with timevarying delays in states. We obtain sufficient conditions for the existence of kth order$H^{\infty}$ controllers in terms of three linear matrix ineualities(LMIs). These sufficient conditions are dependent on the maximum value of the time derivative of timevarying delay. Furthermore, we briefly explain how to construct such controllers from the positive definite solutions of their LMIs and give an example.e. 
In this paper, we consider the decentralized reducedorder H
$_{\infty}$ controller for the general plant. Simplifying method is suggested for the general plant with the decentralized controller structure. When the controller is reconstructed for the original system, the decentralizability of the controller for the transformed system is generally destroyed with the older method. We solve this problem. For the simplified system, the structure of the decentralized controller is suggested.. 
Worstcase state estimation will be proposed in this paper. By using the worstcase disturbance and worstcase state estimation, we can obtain right/left constrained coprime factors. If constrained coprime factors are used in designing a controller, the infinitynorm of closedloop transfer matrix can be smaller than any constant .gamma.(> .gamma.
$_{opt}$ ) without matrix dilation optimization. The derivation of left/right constrained coprime factors is achieved by doubly coprime factorization for the plant constrained by the infinity norm. And the parameterization of stabilizing controllers gives us easily understanding for H$_{\infty}$ control theory.ry. 
This study deals with the nonlinear H
$_{\infty}$ control problem of linear system using nonlinear weight. Generally the solvable condition of nonlinear H$_{\infty}$ control problem is given by the Hamilton Jacobi equality or inequality, but it is very difficult to solve. In this study, some constraints of nonlinear weight reduce the solvable condition to linear Riccati equation. Some examples of the control system design using nonlinear weight are shown.n. 
In this note, we propose the discrete model reduction method over disctype analytic domains. We define Hankel singular value over the disc that is mapped by standard bilinear mapping. And GSPA(generalized singular perturbation approximation) and DT(direct truncation) are generalized to GSPA and DT over a disc. Furthermore we show that the reduced order model over a smaller domain has a smaller L
$_{\infty}$ norm error bound.. 
This paper considers a global resolution of kinematic redundancy under inequality constraints as a constrained optimal control. In this formulation, joint limits and obstacles are regarded as state variable inequality constraints, and joint velocity limits as control variable inequality constraints. Necessary and sufficient conditions are derived by using Pontryagin's minimum principle and penalty function method. These conditions leads to a twopoint boundaryvalue problem (TPBVP) with natural, periodic and inequality boundary conditions. In order to solve the TPBVP and to find a global minimum, a numerical algorithm, named twostage algorithm, is presented. Given initial joint pose, the first stage finds the optimal joint trajectory and its corresponding minimum performance cost. The second stage searches for the optimal initial joint pose with globally minimum cost in the selfmotion manifold. The effectiveness of the proposed algorithm is demonstrated through a simulation with a 3dof planar redundant manipulator.

An impedance control approach based on an extended task space formulation is addressed to control the kinematically redundant manipulators. Defining a weighted inner product in joint space, a minimal parametrization of the null space can be achieved and we can visualize the null space motion explicitly. Based on this formulation, we propose a control method called inertially decoupled impedance controller to control the motion of the endeffector as well as the internal motion expanding the conventional impedance control. Some numerical simulations are given to demonstrate the performance of the proposed control method.

This paper is concerned with how to utilize kinematic redundancy to reconstruct the inverse kinematic solution which is not attainable due to hardware limitations. By analyzing the error due to hardware limitations, we are to show that the recoverability of limitation reduces to the solvability of a reconstruction equation under the feasibility condition. It will be next shown that the reconstruction equation is solvable if the configuration is not a jointlimit singularity. The reconstruction method will be proposed based on the geometrical analysis of recoverability of hardware limitations. The method has the feature that no task motion error is induced by the hardware limitations while minimizing a possible null motion error, under the recoverability assumed.

We propose a mathematical model which describes the walking behavior of a person and to analyze the effect of the personality on the dynamics of the crowd. The fundamental assumption is that the human behavior is not a random process but a deterministic process with several basic mechanisms and each fundamental mechanism is common and only the parameter is different from person to person. The proposed model is based on the servomechanism which drives a person along the planned path from point to point. This model has been applied to simulate the walks of people in a crowd and the simulated results have a good coincidence with actual measurement.

Inherently safe plants are maintained through the systematic identification of potential hazards, and various hazard evaluation methods have been developed. Recently, much effort is given into the development of automated hazard evaluation system by introducing the expert system. An automated system will help to obtain consistency and to make the result more reliable. HAZOP study is one of the most systematic and logical evaluation procedure. However, it has disadvantages: experts should participate at the same time, the detailed study requires much manhour, and the results depend on the expertise of the experts. Therefore, the automation of hazard evaluation is necessary to reduce the required time and to get the consistent evaluation results. In this study, HAxSYM, an expert system to automate HAZOP study, is developed. The case studies are performed to validate the effectiveness of the developed system, and the results are compared to the results of traditional method.

This paper presents an approach to estimation of learning gain in iterative learning control for discretetime affine nonlinear systems. In iterative learning control, to determine learning gain satisfying the convergence condition, we have to know the system model. In the proposed method, the inputoutput equation of a system is identified by neural network refered to as Piecewise Linearly Trained Network (PLTN). Then from the inputoutput equation, the learning gain in iterative learning law is estimated. The validity of our method is demonstrated by simulations.

Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated nodes and multibranches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed by ordinary first order difference equations with one sampling time delay. It has been already reported that learning algorithm of parameter variables in U.L.N. by forward and backward propagation is useful for modeling, managing and controlling of the large scale complicated systems such as industrial plants, economic, social and life phenomena. But, in the previous learning algorithm of U.L.N., time delays between the nodes were fixed, in other words, criterion function of U.L.N. was improved by adjusting only parameter variables. In this paper, a new learning algorithm is proposed, where not only parameter variables but also time delays between the nodes can be adjusted. Because time delays are integral numbers, adjustment of time delays can be carried out by a kind of random search procedure which executes intensified and diversified search in a single framework.

A novel iterative learning control scheme comprising a unique feedforward learning controller and a disturbance observer is proposed. Disturbance observer compensates disturbance due to parameter variations, mechanical nonlinearities, unmodeled dynamics and external disturbances. The convergence and robustness of the proposed controller is proved by the method based on Lyapunov stability theorem. The results of numerical simulation are shown to verify the effectiveness of the proposed control scheme.

This paper presents an iterative fuzzy learning control scheme which is applicable to a broad class of nonlinear systems. The control scheme achieves system stability and boundedness by using the linear feedback plus adaptive fuzzy controller and achieves precise tracking by using the iterative learning rules. The switching mode control unit is added to the adaptive fuzzy controller in order to compensate for the error that has been inevitably introduced from the fuzzy approximation of the nonlinear part. It also obviates any supervisory control action in the adaptive fuzzy controller which normally requires high gain signal. The learning control algorithm obviates any output derivative terms which are vulnerable to noise.

Continuing advances in the formulation and solution of risksensitive control problems have reached a point at which this topic is becoming one of the more intriguing modern paradigms of feedback thought. Despite a prevailing atmosphere of close scrutiny of theoretical studies, the risksensitive body of knowledge is growing. Moreover, from the point of view of applications, the detailed properties of risksensitive design are only now beginning to be worked out. Accordingly, the time seems to be right for a survey of the historical underpinnings of the subject. This paper addresses the beginnings and the evolution, over the first quartercentury or so, and points out the close relationship of the topic with the notion of optimal cost cumulates, in particular the cost variance. It is to be expected that, in due course, some duality will appear between these notions and those in estimation and filtering. The purpose of this document is to help to lay a framework for that eventuality.

This paper proposes a robust control method using Universal Learning Network(U.L.N.) and second order derivatives of U.L.N.. Robust control considered here is defined as follows. Even if external input (equal to reference input in this paper) to the system at control stage changes awfully from that at learning stage, the system can be controlled so as to maintain a good performance. In order to realize such a robust control, a new term concerning the perturbation is added to a usual criterion function. And parameter variables are adjusted so as to minimize the above mentioned criterion function using the second order derivative of the criterion function with respect to the parameters.

This paper studies on an active noise control to reduce noise sound level in a small cavity. Ideally, high gain control solves this problem, but, in practice, there exist nonlinear characteristics and modelling errors of the small cavity, which make the control more complicated. H
$_{\infty}$ control can be used in an uncertain system after determining uncertain boundary and solved algebraically or numerically. In this paper, the numerical one, LMI(Linear Matrix Inequality), is used to get controller. Finally, experiment result shows the performance of the controller.. 
The recently proposed control method using a Lyapunovlike function can give global asymptotic stability to a system with mismatched uncertainties if the uncertainties are bounded by a known function and the uncontrolled system is locally and asymptotically stable. In this paper, we modify the method so that it can be applied to a system not satisfying the latter condition without deteriorating qualitative performance. The assured stability in this case is uniform ultimate boundedness which is as useful as global asymptotic stability in the sense that it is global and the bound can be taken arbitrarily small. By the proposed control law we can deal with both matched and mismatched uncertain systems. The above facts conclude that Lyapunovlike control method is superior to any other Lyapunov direct methods in its applicability to uncertain systems.

Kinematically redundant manipulators have been studied because of its usefulness of kinematic redundancy. It is natural that the kinematic redundancy induces a kind of control redundancy. By using the weighted kinematically decoupled joint space decomposition, we unify the control redundancy and the kinematic redundancy parameterized by the joint space weighting matrix. Concentrating to the particular component of each decomposition, we can describe the local minimization behavior of the control weighted quadratic by each weighted decomposition. The result extends the conventional results on general setting, and should be of interest in understanding the motion behavior of kinematically redundant manipulators.

There is a tendency nowadays to produce increasingly miniaturized electronic equipment which incorporate parts that have to be precisely positioned, like lenses, heads and CCD's in scanners, printers, copiers, VCR's, optical fiber modules, etc. In contrast to the production process of precision parts, which is currently being carried out automatically, the assemblage process is still being performed by specially skilled technicians. The assemblage process comprises normally the following steps: firstly, the parts are roughly positioned and partially fixed, secondly, the parts are manually nudged towards the target position and finally glued, screwed or welded. This paper presents a system that uses six piezo Impact Drive Mechanisms for accurate micro positioning within three degrees of freedom (lateral and longitudinal translation and rotation). The system is designed to positioning a printed circuit board with an accuracy better than 3 .mu.m (for translations), 5 mrad (for rotation).

The nozzle dam task is essentially needed to maintain and repair nuclear power plants. For this task, an 8dof redundant robot is studied with a local pathplanning method[l] which is effective to find the optimal joint path in the constrained environment. In this paper, the method[l] is improved practically with the weight matrix and efficient algorithm to find working set. The effectiveness of the proposed method is demonstrated by simulation and animation.

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) lineblob extraction, (4) linefeature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squaresbased method and the principal axisbased method on the computation of line orientation. We show its efficiency with some real images.al images.

This study deals with the problem of the recognition of the preceding vehicles by image processing. The purpose of this study is the development of the equipment to prevent a collision with preceding vehicles during driving the vehicle. In order to decrease the processing time and increase reliability, at first, the traffic lane is extracted. It is determined by detecting road edges and calculating their tangent. After the traffic lane is gotten, the position of the vehicle is searched inside the lane. The features used to detect the vehicles in the algorithm are shadow of the vehicle, vertical edges, horizontal edges, and symmetrical segment. The preceding vehicles are extracted successfully by this method.

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

In this paper, the authors propose a new method for linearizing a nonlinear dynamical system by use of Volterra kernel of the nonlinear system. The authors have recently obtained a new method for measuring Volterra kernels of nonlinear control systems by use of a pseudorandom Msequence and correlation technique. In this method, an Msequence is applied to the nonlinear system and the crosscorrelation function between the input and the output gives us every crosssection of Volterra kernels up to 3rd order. Once we can get Volterra kernels of nonlinear system, we can construct a linearization method of the nonlinear system. Simulation results show good agreement between the observed results and the theoretical considerations.

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.

Physical systems axe generally continuoustime in nature. However as the data measured from these systems is generally in the form of discrete samples, and most modern signal processing is performed in the discretetime domain, discretetime models are employed. This paper describes methods for estimating the coefficients of continuoustime system within a closed loop control system. The method employs a recursive estimation algorithm to identify the coefficients of a discretetime bilinearoperator model. The coefficients of the discretetime bilinearoperator model closely approximate those of the corresponding continuoustime Laplace transform transfer function.

The authors have recently proposed a new method for identifying Volterra kernels of nonlinear control systems by use of Msequence and correlation technique. A specially chosen Msequence is added to the nonlinear system to be identified, and the crosscorrelation function between the input and output is calculated. Then every crosssection of Volterra kernels up to 3rd order appears at a specified delay time point in the crosscorrelation. This method is applied to a saturationtype nonlinear feedback control system of mechanicalelectrical servo system having torque saturation nonlinearity. Simulation experiments show that we can obtain Volterra kernels of saturationtype nonlinear system, and a good agreement is observed between the observed output and the calculated one from the measured Volterra kernels.

In this paper, we propose a design method of PID adaptive controller based on frequency domain analysis. The method is based on the estimation of a nonparametric process model in the frequency domain and the determination of the PID controller parameters by achieving partial model matching so as to minimize a performance function concerning to relative model error between the loop transfer function of the control system and the desired system. In the design method the process is represented only by a discrete set of points on the Nyquist curve of the process. Therefore it is not necessary to estimate a full order parameterized process model.

A modified output error method developed by the authors are presented, and an example of its application on an air accident is shown. In order to obtain the aerodynamic coefficients of an aircraft, the maximum likelihood method and the output error method are often employee However, in the case of an air accident, there is only one flight data available. The newly devised modified output error method by authors seems to have shown fine performance. By employing this method and processing the flight data, unstational aerodynamic coefficients are obtained. The contradiction between the recorded flight data and the circumstantial evidence was reasonably explained.

This paper deals with the problem of designing an adaptive regulator in order to improve transient performance in timeresponse when the linear statespace model of the plant contains unknown parameters which vary within prescribed bounds. The whole possible parameter space is divided into some subspaces and multiple models and controllers are established from the view point that each controller gives satisfactory transient behavior for systems corresponding to each parameter subspace. Based on timeresponse and an associated cost function, an appropriate controller is selected online out of multiple controllers.

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closedloop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

This paper deals with the design problem of model reference adaptive controllers for MIMO plants with unknown orders. A design scheme for an adaptive control system based on CGT theorem, which has hierarchical structures derived from backstepping strategies, is proposed for MIMO plants with unknown orders but with known relative MacMillan degrees(relative degrees for SISO plants). It is also shown that all the signals in the resulting control system are bounded, and that the asymptotic tracking is achieved in the case where reference inputs are step.

In this paper, a fuzzy PNN algorithm is proposed to estimate the structure and parameters of fuzzy model, using the PNN based on GMDH algorithm. New algorithm uses PNN algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the leastsquare method in order to identify the optimal consequence parameters. Both time series data for gas furnace and data for wastewater treatment process are used for the purpose of evaluating the performance of the fuzzy PNN. The results show that the proposed technique can produce the fuzzy model with higher accuracy than other works achieved previously.

This paper presents a systematic approach to identify a linguistic fuzzy model for a multiinput and singleoutput complex system. Such a model is composed of fuzzy rules, and its output is inferred by the simplified reasoning. The structure and membership function parameters for a fuzzy model are automatically and simultaneously identified by GA (Genetic Algorithm). After GA search, optimal parameters for the fuzzy model are finely tuned by a gradient method. A numerical example is provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce the linguistic fuzzy model with higher accuracy and a smaller number of rules than the ones achieved previously in other methods.

A pneumatic cylinder has been used in the production facilities of various industries. However, it is difficult to achieve deciding the precise position of the piston rod, due to the nonlinear properties arising from the air compression and the friction. In recent years, the fuzzy control algorithm has been frequently applied to various kinds of systems on account of its simple algorithm, good adaptability to complex or nonlinear systems and so on. On the other hand, the PID or IPD control has been used in many engineering fields because of the excellent performance. However, it is known that each one of them has disadvantages. In this paper, we propose a hybrid control which is strived to obtain the advantages of each other. It is shown that the proposed hybrid control performs better than the conventional IPD control through the experimental results.

This paper considers feedback error learning neural networks for robot manipulator control. Feedback error learning proposed by Kawato [2,3,5] is a useful learning control scheme, if nonlinear subsystems (or basis functions) consisting of the robot dynamic equation are known exactly. However, in practice, unmodeled uncertainties and disturbances deteriorate the control performance. Hence, we presents a robust feedback error learning scheme which add robustifying control signal to overcome such effects. After the learning rule is derived, the stability is analyzed using Lyapunov method.

This paper presents a new information processing machine which is called artificial brain(ABrain) and considers the structure of artificial neural networks constructed in a RICOH neurocomputer RN2000 in the ABrain, in order to track given trajectories which are produced in a microcomputer or a moving light by hand in a recognition and tracking system.

This paper describes the analysis of the operation of the switched snubber in order to depress the surge voltage in the MOSFET inverter. In this paper, the Nchannel MOSFET which operates faster than the Pchannel MOSFET was used for the inverter circuit. So, the inverter and switched snubber can operate at highfrequency in the order of MHz. The cause of generating the surge voltage in the high frequency inverter has been cleared, and then how to depress the surge voltage using the switched snubber consisting of an Nchannel MOSFET has been given. Furthermore, described is the power loss within the switched snubber which is made of an Nchannel MOSFET. The inverter having the Nchannel MOSFET used as a switched snubber can drive such a low impedance load such as megasonic transducer for a megasonic studied cleaner sufficiently.

The color matching of the paints are difficults for the three items of the issues, i.e., the variation of surroundings, the form of vane, and the rotative velocities of the vane. A new color matching system improved to the three items of the issues has constructed by the present study.

In work scheduling problems, scheduling constraints are not absolutely rigid; they may be changed depending on the scheduling aspect effected. In order to cope with changes in scheduling constraints and assignment strategies and to optimize scheduling results quickly, this paper will propose a new scheduling method which combines knowledge engineering and mathematical programming techniques.

Authors ahve developed ALFLEX simulation program which can implement the flight simulation ad control system design of ALFLEX efficiently by using aerodynamic data provided by NAL/NASDA. Then we have designed and example of flight path and altitude control system of ALFLEX. The philosophy of the design method is explained in detail, and a flight simulation result is shown, which verifies the fine performance of the system.

The moving vehicle with disturbances has the 6 dof motion in the pitching, yawing and rolling directions of two independent axes. The control system in such a moving vehicle has to perform disturbance rejection well. The paper presents PID controller with disturbance rejection function, low sensitivity filter and notch the bending frequency rejection. The performance of a designed system has been certified by the simulation and experiment results.

The paper highlights the need for cautious least squares estimation when dealing with industrial applications of bilinear selftuning control and indicates in qualitative terms the benefits of the approach over linear selftuning control schemes. The cautious least squares algorithm is described and the use of cautious selftuning in the context of both commissioning and implementation discussed.

This paper considers the output regulation problems on uncertain systems. Using NRestimator(online), a family of equilibrium points for the uncertain system is computed. The state variables of the closed loop system track the average value of the obtained equilibrium manifold by dynamic state feedback control.

In this paper, a new optimization method which is a kind of random searching is presented. The proposed method is called RasVal which is an abbreviation of Random Search Method with Variable Seaxch Length and it can search for a global minimum based on the probability density functions of searching, which can be modified using informations on success or failure of the past searching in order to execute intensified and diversified searching. By applying the proposed method to a nonlinear crane control system which can be controlled by the Universal Learning Network with radial basis function(R.B.P.), it has been proved that RasVal is superior in performance to the commonly used back propagation learning algorithm.

A model following control system(MFCS) can give general output signals following desired ones. In previous studies, a method of nonlinear MFCS was proposed by S.Okubo[1]. In this paper, the method of nonlinear MFCS will be extended to discrete time nonlinear systems. It is easy to extend the method to discrete time systems. But in the case .gamma.=1 discrete time systems, the proof becomes difficult, because the transfer function from f(v(k)) to v(k) can't be a positive real function. In this case, to ensure that internal states are stable, a new criterion is proposed.

Modular robot manipulator is a robotic system assembled from discrete joints and links into one of many possible manipulator configurations. This paper describes the design method of newly developed modular robot manipulator and the methodology of a task based reconfiguration of it. New locking mechanism is proposed and it provides quick coupling and decoupling. A parallel connection method is devised and it makes modular robot manipulator working well and the number of components on each module reduced. To automatically determine a sufficient or optimal arrangement of the modules for a given task, we also devise an algorithm that automatically generates forward and inverse manipulator kinematics, and we propose an algorithm which maps task specifications to the optimized manipulator configurations. Efficient genetic algorithms are generated and used to search for a optimal manipulator from task specifications. A few of design examples are shown.

In this paper, we have examined the impedance characteristics of a tipper link of human being in a positioning motion. Firstly, we have shown the characteristics of the human arm using a bilinear model. From the bilinear model, we have observed that both the driving torque of the forearm and the viscoelasticity of the elbow joint can be controlled by muscles, respectively. Then, we have defined several indexes to show the impedance characteristics. Using the proposed indexes, we have examined the impedance characteristics in the positioning operation. As a result, we can not observe the difference of the impedance characteristics, even if the ease of the positioning motion is varied.

We propose a coordinated motion control algorithm of dual manipulators handling a flexible object. The controller is designed so that it can specify the apparent impedance of the object as well as can control its deformation. The experimental results will illustrate validity of the proposed algorithm.

This paper describes a DC voltage controller for the DC power supply which is constructed using the fullbridged MOSFET DCtoRF power inverter and rectifier. The fullbridged MOSFET DCtoRF inverter consisting of four MOSFET arrays and an output power transformer has a control function which is able to control the RF output power when the widths of the pulse voltages which are fed to four MOSFET arrays of the fallbridged inverter are changed using the pulse width control circuit. The power conversion efficiency of the fullbridged MOSFET DCtoRF power inverter was approximately 85 % when the duty cycles of the pulse voltages were changed from 30 % to 50 %. The RF output voltage from the fullbridged MOSFET DCtoRF inverter is fed to the rectifier circuit through the output transformer. The rectifier circuit consists of GaAs schottky diodes and filters, each of which is made of a coil and capacitors. The power conversion efficiency of the rectifier circuit was over 80 % when the duty cycles of the pulse voltages were changed from 30 % to 50 %. The output voltage of the rectifier circuit was changed from 34.7V to 37.6 V when the duty cycles of the pulse voltages were changed from 30 % to 50 %.

This paper proposes an approach in modeling a 4x60inch Allis Chalmers Hydrocone Crusher [1] hydroset and presents some numerical simulation results. The mining and quarry industry is one of the industries which extensively use hydrocone crushers, which are a family of cone crushers, for rock size reduction. Field studies have proved that if proper control and management of these machines is undertaken, they can yield an increased production output of more than 30%, in addition substantial savings in both energy consumption per unit ton produced and manpower can be easily realized. In order to achieve these economic benefits, high performance from these machines is expected. Implementing automatic control for such machines would be a great leap towards achieving both economic benefits and more effective foolproof predictive maintenance. But, unfortunately, for such a control system to be designed, it necessary to make a mechatronical model of this plant. The plant model is able to give us an insight into variations of both the plant gap setting (displacement) and system pressure due to variable loading arising from the crushing process.

A method to determine an optimal temperature trajectory that guarantees polymer products having controlled molecular weight distribution and desired values of molecular weight is presented. The coordinate transformation method and the optimal control theory are applied to a batch PMMA polymerization system to calculate the optimal temperature trajectory. Coordinate transformation method converts the original fixedendpoint, freeendtime problem to a freeendpoint, fixedendtime problem. The idea is that by making the reactor temperature track the optimal temperature trajectory one may be able to produce polymer products having the prespecified physical property in a minimum time. The online control experiments with the PID control algorithm have been conducted to establish the validity of the scheme proposed in this study. The experimental results show that prespecified polymer product could be obtained with tracking the calculated optimal temperature trajectory.

This paper reports about the successful suspension of a glass plate by electrostatic forces. In order to implement a stable suspension, the electrostatic forces exerted on the glass plate are actively controlled on the basis of the gap lengths between the glass plate and the stator electrodes. In this paper, the dynamic model of the suspension system and the influence of the resistivity of glass on the system stability are described, followed by stator electrode design, the experimental apparatus and a stabilizing controller. Experimental results show that the glass plate can be suspended at a gap length of about 0.3 mm. The influence of air humidity on the suspension initiation time, and the lateral dynamic characteristic are also described.

In this paper we made a reliability analysis of power system pumps by using the dimensional reduction method which over comes the problem due to unavailability of enpugh data in the actual systems under many different operational environments. Hence a resonable method was proposed to determine the optimum maintenance interval of given pump in thermal power stations. This analysis was based on an actual data set of pumps for over ten years in thermal power stations belonged to Kyushu Electric Power Company, Japan.

This fault diagnosis system consists of qualitative models, qualitative interpreter, and inference engine. Qualitative models are formed by analysis of the relationships between faults and behaviors of sensor trends, which are described by state transition trees. Qualitative interpreter outputs confidence factors with three qualitative quantities which represent the states of sensor trends. And then, the possible faults are detected by inference module which matches the states of trends within a window size with the qualitative models using the wellknown minmax operation.

The authors have already proposed a method for grouping of inputs of a logical circuit under test (LCUT) by use of Msequence correlation. We call this method as input grouping (IG) method. In this paper, the authors propose a new method to estimate the faulty part in the circuit by use of IG when some information on the candidate of faulty part can be obtained beforehand. The relationship between IG and fault probabilities of a LCUT, and undetected fault ratios are investigated for various cases. Especially the investigation was made in case where the IG was calculated by use of n correlation functions (I
$G_{inp}$ ). From the theoretical study and simulation results it is shown that the estimation error ratio of fault probabilities and undetected fault ratio of LCUT are sufficiently small even when only a part of correlation functions are used. It is shown that the number of correlation functions which are to be memorized to calculate IG can be considerably reducible from 2$^{n}$  1 to n by use of I$G_{inp}$ . So this method would be very useful for a fault diagnosis of actual logic circuit.uit. 
This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, faulteffect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.

Fault diagnosis problem is currently the subject of extensive research and numerous survey paper can be found. Although several works are studied on the fault detection and isolation observers and the residual generators, those are concerned with only the detection of actuator failures or sensor failures. So, the perfect detection and isolation is strongly required for practical applications. In this paper, a, strategy of fault diagnosis using multiple proportional integral (PI) observers including the magnitude of actuator failures is provided. It is shown that actuator failures are detected and isolated perfectly by monitoring the integrated error between actual output and estimated output by a PI observer. Also in presence of complex actuator and sensor failures, these failures are detected and isolated by multiple PI observers.

By far the PID controller is most widely sed in the process industries. However, current tuning methods yield PID parameters only for a restricted class of process models. There is no general methodology of PID controller tuning for arbitrary process models. In this paper, we generalize the IMCPID approach and obtain the PID parameters for general models by approximating the ideal controller with a Maclaurin series. Further, the PID controller tuned by the proposed PID tuning method gave more closer closedloop response to the desired response than those tuned by other tuning methods.

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

A control algorithm is proposed for nonlinear multiinput multioutput(MIMO) batch processes by combining quadratic iterative learning control(QILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedbackonly control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

We propose a robust tuning method of the quadratic criterion based iterative learning control(QILC) algorithm for discretetime linear batch system. First, we establish the frequency domain representation for batch systems. Next, a robust convergence condition is derived in the frequency domain. Based on this condition, we propose to optimize the weighting matrices such that the upper bound of the robustness measure is minimized. Through numerical simulation, it is shown that the designed learning filter restores robustness under significant model uncertainty.

In this paper, we deal with some numerical analyses of a reentry vehicle in a 2dimensional plane as an optimal control problem. To reduce the dynamic load, the heat load and the oscillation in the trajectory, we researched the trajectories in which the load factor or the rate of flight path angle was minimized during reentry. In addition to that, taking advantage of the monotonous subarc method and the folded timeaxis method, we tried to find the heatless and loadless trajectory with combinations of some sectional functionals so that we can achieve more comfortability.

In contactless disk handling systems based on electrostatic suspension in which the stator is to be transferred, the limited stiffness in lateral direction severely restricts the achievable translational acceleration. In existing stator electrode pattern designs, the magnitude of the lateral force is determined by the magnitude of the control voltages which are applied to the individual electrodes to levitate the disk stably. As a result, the lateral force cannot be set arbitrarily. A new stator electrode pattern is presented for the electrostatic levitation of diskshaped objects, in particular silicon wafers and aluminum hard disks, which allows the lateral forces to be controlled independently from the levitation voltages. Therefore, greater lateral forces can be obtained, compared with the existing stator designs. Experimental results will be presented for a 4inch silicon wafer that clearly reveal the increased lateral stiffness by using the proposed stator electrode compared to the conventional electrode pattern.

In this paper a new positioning method for cylindrical work pieces on rotating supports is studied. A work piece on a rotating axis is positioned by an impact drive mechanism (IDM) whose driving parameters are steadily updated by observing the object movement. The application of this actuator and the use of a multifunctional PC board for all necessary input and output operations such as e.g. data acquisition or wave form generation allow an alignment with a precision of less than 1.mu.m in a relatively short time and at low cost compared to conventional methods.

A new steelmaking process, stripcasting, is introduced. The stripcasting is a new technique making the thin steel strip from the molten steel directly without resorting to repetitive reheating and hotrolling required in a conventional steelmaking method. This paper derives the mathematical model of strip caster, proposes a control strategy for stable startup operation and a fuzzy decision making rule for automatic control mode change in stripcasting process.

This paper describes the robust controller design methods applied to the problem of an automatic system for towvehicle/trailer combinations. This study followed an inverse Linear Quadratic Regulator(LQR) approach which combines pole assignment methods with conventional LOR methods. It overcomes two concerns associated with these separate methods. It overcomes the robustness problems associated with pole placement methods and trial and error required in the application of the LQR problem. Moreover, a Kalman filter is used as the observer, but is modified by using the loop transfer recovery (LTR) technique with modified transmission zero assignment. The proposed inverse LQG,/LTR controllers enhances the forward motion stability and maneuverability of the combination vehicles. At high speeds, where the inherent yaw damping of the vehicle system decreases, the controller operates to maintain an adequate level of yaw damping. At backward moton, both 4WS (2WS towvehicle, 2WS trailer) and 6WS (4WS towvehicle, 2WS trailer) control laws are proposed by using inverse LQG/LTR method. To evaluate the stability and robustness of the proposed controllers, simulations for both forward and backward motion were conducted using a detailed nonlinear model. The proposed controllers are significantly more robust than the previous controllers and continues to operate effectively in spite of parameter perturbations that would cause previous controllers to enters limit cycles or to loose stability.

In this paper, we propose a new method to estimate robot position without landmark. At first, it is studied to estimate robot state using Markov decision rule. And, a matching method is discussed for estimating current position more accurately under the estimated current state. At second, we combine or fuse the matching method with the POMDP method in order to estimate the position under a dynamically changing environment. Finally we will show that our method can estimate the position precisely and robustly of which error are not cumulated through simulation results.

This is a paper intended for initial stage of vehicle modeling and design. The needs to determine a variety of vehicle suspension parameters required for initial design has been difficult and timeconsuming task. In order to facilitate a concise and efficient presentation of initial vehicle design procedure, this paper uses a mathematical model and physical geometry. Vehicle model consists of dimensions, inertias and mechanical constants. These vehicle model parameters divided into several categories : basic parameters, coefficients and constants, design specification, spring and damper, bush stiffness, stabilizer bar, suspension geometry, tire, and vehicle weights of various design condition. This paper uses a vehicle design fundamental (VDF) program running under Windows 95 graphical interface. The features of VDF will be briefly outlined in this paper.

A neural fuzzy control strategy, developed in order to make a Mobile Vehicle(MV) run along with the traffic guidelines on the road, is presented. A neurocomputer is used in the control procedure and it learnt the driving knowledge to control the MV's actions. The image information of the guidelines is provided by a CCD camera on the top of the MV. The MV utilize the image information to identify the shape of the road and to decide the position of itself, and control the running actions. A fuzzy controller works online. Both of the neural controller and the fuzzy controller make up each other. This control method solve the problem of mechanical and electrical inertia and make the Mobile Vehicle run rapidly and smoothly.

This paper is dealing with a design of linear controller so that the plant output is regulated to follow a reference model output when the plant equation is described by a class of nonlinear timevarying control systems.

In this paper development of a CAD of control systems is introduced which enables us to do not only analysis of control systems, design of controllers but also realtime implementation of controllers. By utilizing this software, the control engineer is able to repeat the procedure of modification of controllers and experiments without recompile to attain better performance. The software also offers the facility to update the parameters of controllers without stopping realtime control, which helps online tuning of controllers. If some parameters of the controller is changed online, the control input may change discontinuously. It has serious effect on the control systems. A method for online tuning of state feedback controller with state observer is proposed and verified through the experiment with an inverted pendulum.

In this paper, based on the performance analysis of serial production lines with quality inspection machines, we develope an buffer size optimization method to maximize the production rate. The total sum of buffer sizes are given and a constant, and under this constraint, using the linear approximation method, we suggest a closed form solution for the optimization problem with an acceptable error. Also, we show that the upstream and downstream buffers of the worst performance machine have a significant effect on the production rate. Finally, the suggested methods are validated by simulations.

Virtual Manufacturing System(VMS) is an integrated computer based model which has physical, logical schema and behavior of real manufacturing system. In this paper, an integrated scheduling system is developed to simulate and control a Virtual Factory. A workflow model is constructed to define and analyze the structure of a VMS. Online dynamic dispatching system is developed using MultiPass algorithm and scheduling system considering dynamic CAPP is carried out. Integrated scheduling system developed in this paper reduces the discrepancies between virtual model and real manufacturing system, and control of real shop floor is possible.

In this paper, we discuss decentralized optimal fault tolerant supervisory control issues on the basis of failure analysis and diagnosis from the angle of discrete event dynamic system. We address the detectability and the observability problems, and develope fault tolerant supervisory control system upon the failure analysis and diagnosis schemes. A complete mincut is introduced and the procedure for finding the achievable or nonachievable layered optimal legal sublanguages is suggested for a preferential option among the reachable states in the controlled plant. A layered optimal supervisory control framework is proposed upon these. We extend the concept of decentralized supervisory control by considering the problem of combination of decentralized with centralized control in case pure decentralized control happens to be inadequate. We introduce the concept of locally controllable pair and present a hybrid decentralized supervisory control framework. Finally, we propose the analytical framework for a decentralized optimal fault tolerant supervisory control systems.

In this paper, the eigenstructure of a class of linear time varying systems, termed as linear quasitime invariant(LQTI) systems, is investigated. A system composed of dynamic devices such as linear time varying capacitors and resistors can be an example of the class. To effectively describe and analyze the LQTI systems, a generalized differential operator G is introduced. Then the dynamic systems described by the operator G are studied in terms of eigenvalue, frequency characteristics, stability and an extended convolution. Some basic attributes of the operator G are compared with those of the differential operator D. Also the corresponding generalized Laplace transform pair is defined and relevant properties are derived for frequency domain analysis of the systems under consideration. As an application example, a LQTI circuit is examined by using the concept of eigenstructure of LQTI system. The LQTI filter processes the sinusoidal signals modulated by some functions.

In this paper, a feedforwardplusfeedback control scheme is presented to prevent congestion in storeandforward packet switching networks. The control scheme consists of two algorithms. Specifically, the input traffic adjustment algorithm employs a fairness policy such that the transmission rate of the input traffic is proportional to its offered rate. The control signal computation algorithms to ensure stability of the overall system in the robust sense and to ensure the desired transient behavior in the adaptive, with respect to variations of input traffic, are designed.

In this paper, a designing method of model following control system for linear descriptor system with disturbances is proposed. The features of this method are:1) both the physical structure of the system and the physical system variables properties can be preserved because there is no necessary to make transformation of this system. 2) boundedness of internal states are proved by means of coprime factorization of descriptor system.

Synthesis for qualitative analysis in connection with quantitative analysis from the pinch design method, EVOP and Operations Research is proposed for the optimal synthesis of heat exchanger networks, that is through of the transportation model of the linear programming for synthesizing chemical processing systems, to determine the location of pinch points, the stream matches and the corresponding heat flowrate exchanged at each match. In the second place, according to the optimization, the optimal design of heat transfer enhancement is carried on a fixed optimum heat exchanger network structure, in which this design determines optimal operational parameters and the chosen type of heat exchangers as well. Finally, the method of this paper is applied to the study of the optimal synthetic design of heat exchanger network of constantdecompress distillation plants.

This paper represents an adaptive position controller with the disturbance observer for multiaxis servo system. The overall control system consists of three parts : the position controller, the disturbance observer with free parameters and crosscoupled controller which enhances contouring performance by reducing errors. Using twodegreesof freedom conception, we design the command input response and the closed loop characteristics independently. The servo system can improve the closed loop characteristics without affecting the command input response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer. Moreover, the crosscoupled controller enhances tracking performance. Thus total position control performance is improved. Finally, the performance of the proposed controller shows that it improves the contouring performance along with the reference trajectory in the XYtable.

A time delay controller with state feedback is proposed for azimuth motion control of the frictionless positioning device which is subject to the variations of inertia in the presence of measurement noise. The time delay controller, which is combined with a lowpass filter to attenuate the effect of measurement noise, ensures the asymptotic stability of the closed loop system. It is found that the lowpass filter tends to increase the robustness in the design of time delay controller as well as the gain and phase margins of the closed loop system. Numerical and experimental results support that the proposed controller guarantees a good tracking performance irrespective of the variation of inertia and the presence of measurement noise.

We propose a method to improve repeatability positioning precision of a linear pulse motor. By using this method the systematic error which may make the precision worse can be suppressed easily. And also we show that Power OPAmp drive system enables the accidental error to be suppressed in comparison with PWM control drive system using IGBT inverter. As a result of the suppression of systematic and accidental error, improved performance of a linear pulse motor with repetitive positioning control is shown by experimental results.

This paper studies electrostatically suspended induction motors (ESIM). The ESIM possesses the rotating ability of an ordinary electrostatic induction motor, in addition to providing contactless support by electrostatic suspension. To accomplish these two functions, a feedback control strategy and the operating principle of an ordinary electrostatic induction motor are used. The stator possesses electrodes which exert the electrostatic forces to the rotor and are divided into a part responsible for suspension and one for rotation. Two rotor types are utilized: a polished glass disk without any surface treatment, and a polished glass disk covered with a thin layer of conductive material (ITO layer) on only one side. In this paper, the principle of the ESIM is described, followed by stator electrode design, experimental apparatus, control strategy for stable suspension. Experimental results show that the glass disk has been rotated with a speed of approximately 70 rpm while being suspended stably at a gap length of 0.3 mm.

In this paper, robust motion control of a flexible microactuator is presented. The actuator is made of a bimorph piezoelectric highpolymer material (PVDF). No mathematical model system can exactly model a physical system such a flexible microactuator. For this reason we must be aware of how modeling errors might adversely affect the performance of a control system for such a model. The H method addresses a wide range of the control problems, combining the frequency and time domain approaches. The design is an optimal one in the sense of minimization of the maximum of the closedloop transfer function. It includes colored measurement and process noise. It also addresses the issues of robustness due to model uncertainties, and is applicable to the, flexible microactuator control problem. Therefore, we adopt the H control problem to the robust motion control of the flexible microactuator. Theoretical and experimental results demonstrate the satisfactory performance and the effectiveness of the designed controller. the effectiveness of the designed controller.

A new method for the electrostatic suspension of diskshaped objects is proposed which is based on a switchedvoltage control scheme. It operates according to a relay feedback control and deploys only a single highvoltage power supply capable of delivering a dc voltage of positive and/or negative polarity. In addition to the unique feature that no highvoltage amplifiers are needed, this method provides a remarkable system simplification relative to conventional methods. It is shown that despite the inherent limit cycle property of relay feedback based control, an excellent performance in vibration suppression is attained due to the presence of a relatively large squeeze film damping. In this paper, the functional principle of the switched voltage control scheme, numerical analysis, stator electrode design, and a nonlinear dynamic model of the suspension system are described. Experimental results will be presented for a 4inch silicon wafer that clearly reveal the capability of the proposed control structure to suspend the wafer stably at an airgap length of 50 .mu.m.

Several papers have already been reported on the flexible manipulator with constant arm length. Some of industrial manipulators, however, have sliding joints. It means that the length of their arm or link varies with time. This paper discusses the trajectory contro lof such a manipulator model, and shows some of the experimental results.

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But the main purposes of the noncontact sensing are rather narrowly confined within object detection and distance measurement. For the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. To resolve these problems in object recognition, an array of the sensor has been used. To improve the spatial resolution, more number of sensors are used in essence throughout the various devices of the sensor arrays. Under the disguise of a fixed number of the sensors, the array can be shifted mechanically in several steps. In this paper we propose a practical sensor resolution enhancement method using an electronic circuit accompanying the sensor array. The circuit changes the transmitter output voltage in several steps. Using the known sensor characteristics, a set of different return echo signals provide enhanced spatial resolution. The improvement is obtained with neither the cost of the increased number of the sensors nor extra mechanical devices.


A new concept of 22.9kV class revenue metering system based on the optical sensing technique was designed and implemented. This paper reports on the performance of a 22.9kV class three phase optical current/voltage metering scheme and three tariff metering system. This optoelectronic system was designed and developed to advance the state of the art in revenue metering. This paper deals with the characteristics of designed optical CPT (Current and Potential Transformer) and optoelectronic demand meter. The extensive field evaluation of the developed system with the existing oil filled transformer and solid state metering pair is undertaking. Upto now the operation of the optical revenue metering system under the field condition compares favorably with the existing system.

The frequencypressure relationship of the cylinder, within 03.0Mpa, is studied by making use of the finite element method (FEM). Based on numerical calculations of FEM and the actual working conditions of the cylinder pressure transducer, this paper presents the optimizing results of the length, the radius and the thickness of the cylinder. Moreover, this paper gives some more important points on designing the whole structure of the cylinder and on reality of the transducer system. The obtained results are of important theoretical bases for developing the cylinder pressure transducer of 03.0Mpa.

In this paper, we propose a simple algorithm to calculate the numbers of the passing cars by using an image processing sensor for the digital black and white images with 256 tone level. Shadow is one of the most troublesome factor in image processing. By differencing the tone level, we cannot discriminate between the body of the car and its shadow. In our proposed algorithm, the area of the shadow is excluded by recognizing the position of each traffic lane. For realtime operation and simple calculation, two lines of the tone level are extracted and the existences of cars are recognized. In the experimental application on a highway, the recognition rate of the realtime operation is more than 94%.

The shape of an object plays a very important role in pattern analysis and classification. Roughly, the researches on this topic can be classified into three fields, i.e. (i) edge detection, (ii) dominant points extraction, and (iii) shape recognition and classification. Many works have been done in these three fields. However, it is very seldom to see the research that discusses the connection relationship of objects. This problem is very important in robot assembly systems. Therefore, here we focus on this problem and discuss how to recover the connection relationship of planar objects. Our method is based on the partial curve identification algorithm. The experiment results show the efficiency and validity of this method.

Symmetry is one of the important structural properties of shapes both in perceptual psychology and in computer vision. Recently, a number of automatic symmetry finding algorithms have been reported. Among them, the algorithm based on the use of principal axes of objects is the most general and practical. It is, however, of no use when shapes concerned have some asymmetry. Asymmetric shapes which make us associate with certain kinds of symmetry are practically important and they are called shapes with potential symmetry in this paper. The algorithm we have already proposed can cope with those shapes having potential axial symmetry. The algorithm employs a reflected image of the original and a certain evaluation function. In the former paper, areal minimization was employed for the evaluation function and it yielded satisfactory experimental results. However, it could not cope with those shapes which have larger asymmetry. In this paper, we propose the employment of variance as an alternative evaluation index with respect to the difference image between the reflected and the original shape. The technique is examined its performance by real video images as well as synthetic data. Experimental results are shown and discussion is given.

Spinal deformity is a serious disease especially for teenagers and it is desirable for school children to be checked possible spinal deformity by moire photographic inspection method. The moire images of children's backs are visually inspected by doctors, which may cause misjudge because of a large amount of data they have to examine. A technique is proposed in this paper for automating this inspection by computer. Two characteristic axes, a potential symmetry axis approximating the human middle line and a principal axis representing the direction of a moire pattern are employed. Two principal axes are extracted locally on a back and their gradients against the potential symmetry axis are calculated. These gradients compose a 2D feature space and a linear discriminant function (LDF) is defined there which separates normal cases from suspicious cases. The LDF defined by 40 training, data was employed in the experiment to examine 40 test data and 77.5% of them were classified correctly. This amounts to 88.8% if the training data is included.

This paper proposes a technique for analyzing mutual relation of an entangled cord by consistent labeling. Cords are often entangled unexpectedly and sometimes they even produce knots. The purpose of this study is to provide an algorithm to resolve such entangled cords automatically. It may as well have applications in future to recognizing the structure of tree branches, angiography, abdominal intestines, etc.