For a safety supervision, watching a restricted area so that no one go there is very important. This has been mostly accomplished by people. They keep an eye on many monitors at onece for a long time. It, however, is too simple and boring to concentrate it for a long time. So it's worth while to construct a watching system by image processing. And the system we made is now actually working at a certain hydroelectric power plant and some other restricted areas in Japan.

This paper describes an outline of pseudorandom M-sequence and its applications to measurement and control engineering. At first, generation and properties of M-sequence is briefly described and then its applications to delay time measurement, information transmission by use of M-array, two dimensional positioning, fault detection of logical circuit, fault detection of RAM, linear and nonlinear system identification.

To establish the sea surface temperature estimation scheme for the upcoming advanced remote sensor, the quasi-analytical solution of the approximated radiative transfer equation which express the radiative transfer process of the radiant energy radiated from the sea surface to the satellite is approximated into the non-linear equation. To solve the simultaneous approximated radiative transfer equation which express the radiative transfer process of the radiant energy radiated from the sea surface to the satellite is approximated into the nonlinear equation. To solve the simultaneous approximated radiative transfer equation at each channel, the constrained non-linear optimization technique is adopted. To define the coefficients of the approximated radiative transfer equation and the constraints, the satellite detected radiance and the total transmittance are computed from the 1350 kinds of simulated atmosphere / surface models via radiative transfer code. The verification from the simulated data show the sufficient result.

The spectrum estimation methods of random processes are expressed in this paper. Beginning with the basic theory, non-parametric and parametric methods are overviewed. As to non-parametric method, numerical calculation method is also discussed. As to parametric method, AR model is a very famous and effective model representing random process. Estimation methods of AR parameters which have been proposed are mentioned here. Wavelet analysis is a recently interested technique in signal processing. An application of wavelet analysis is also shown.

This paper describes a design method of compensators for decentralized control systems. Decentralized control problem is convenient to design multi-variable control systems and formulated as a series of independent designs. The proposed design method is composed of some steps, which is sequentially to close loop of the system diagonalized by regarding interactive subsystem as perturbation for current loop. So, on the basis of H$_{\infty}$ control theory, decentralized controllers are designed considering robust stability for diagonal systems with perturbations. A numerical example shows that the proposed design method is effective for multivariable control systems..

It is well known that the Boyd's theorem states the relation between the imaginary eigenvalues of discriminant H of Riccati equation (A, R, Q) and the singular value of transfer function, but it is only available for R .geq. 0 and Q .geq. 0. In this paper, we extend Boyd's theorem for two case, that is, R is symmetric, Q is sign definite, and R is sign definite, Q is symmetric. We give under the condition that there is a real symmetric solution of Riccati equation the relation between H has imaginary eigenvalue and the maximum eigenvalue of transfer functoin. Finally, we give a necessary and sufficient condition to determine whether H has imaginary eigenvalue under some conditions.

This paper presents a method to accommodate failures that affect aircraft dynamical characteristics, especially control surface jams on a large transport aircraft. The approach is to use the slow effectors, such as the stabilators or engines, in the feedforward manner. The simulation results indicate the performance of the RFCS. In some cases of control surface jam, the aircraft cannot recover without using the stabilators. Although the inputs to the slow effectors are determined using the nominal parameters, the effects of parameter change can be compensated by adjusting the control parameters for the fast surfaces. In the case of rudder jam, if the remaining control surfaces and the differential thrust cancel the moments produced by the stuck rudder, using the engine control improves time responses and reduces deflection angles of the control surfaces. If not, however, the aircraft starts a large rolling motion following a yawing motion. In that case, the stabilators should be used to damp the induced rolliig motion, instead of trying to directly cancel the moments caused by the stuck rudder. Unfortunately, the proposed control law for the stabilators does not give such inputs, because it does not take into account the dynamical effects which stuck surfaces have on the aircraft motions. However, we have shown through simulation that the aircraft can be recovered by giving the stabilators the control inputs that counteract the induced rolling moment. Besides, the method has also been shown through simulation to be effective in maintaining control during a situation similar to an actual accident. Finally let us mention a problem with the RFCS. As stated above, we have not established a method to select a trim point which call be reached as easily as possible using the remaining control effectors. In fact, recovery performance considerably depends on the trim states. As pointed out in Ref. 11, finding the best trim point for impaired aircraft will be one of the most difficult questions in RFCS design.

This paper develops a representation theory of linear systems by means of doubly coprime factorizations, and applies the theory to the simultaneous stabilization problem for a given set of linear systems.

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

A satellite communications monitoring and control system(SCMCS) has been developed at ETRI to provide the capabilities of in-orbit test (IOT) for communications payload and communications system monitoring(CSM) for the satellite communications services. The paper discusses the system level design of SCMCS and its tasks.

To provide more instructive and a safer ground control operation environments for satellite operators, and subsequently to implement a better look-and-feel user interface and a structural mechanism to enhance the efficiency of control and monitoring facilities, we have developed a prototype(laboratory model) ground control softwares targeting for the first generation KOREASAT scheduled to be launched in 1995. As far as the functionality is concerned, the developed system is covering almost all the mission phase operational functions except for some functions like antenna tracking control that are necessary for real operation environments. Most of the functions of the system is realized in softwares but some hardwares needed for TM/TC RF communications are also included in it. The system is now being integrated and under the system test. The performance and functionality is to be evaluated by the end of this year by using the satellite software simulator. Next year, this system could be configured to be used as a workbench for a online/off-line analysis of the operating KOREASAT satellites.

A new method of quaternion feedback control for the attitude acquisition of spacecraft is suggested to limit the angular rates of rigid body which are not desirable and make a control algorithm complicate. New attitude acquisition control algorithm is evaluated and compared with the existing quaternion feedback control method for the large slewing maneuvers through simulations. The simulation results reveal that a new method is effective on limiting the angular rates of spacecraft.

Advanced Real-Time Satellite Simulator(ARTSS) has been developed to support the telemetry, tracking and command operations of the ETRI satellite control system and to provide satellite engineers a more powerful and informative satellite simulations tool on the desktop. To provide extensive simulation functions for a communication satellite system in the pre-operational and operational missions, ARTSS uses a geosynchronous orbit(GEO) satellite model consisting of the attitude and orbit control subsystem, the power subsystem, the thermal subsystem, the telemetry, command and ranging subsystem, and the communications payload subsystem. In this paper, the system features and functions are presented and the satellite subsystem models are explained in detail.

In this study, a high-speed servo valve with no outer leakage is developed, which is used to drive flexible hydraulic actuators (FHA) for extreme environments. In the valve, multilayered PZT devices are used to drive a spool directly and quickly. A bellows is also used to prevent outer leak from the clearance between the spool and the sleeve. Employing a disturbance observer, the lack of the system damping of the valve is improved by feeding back the estimated velocity of the spool, as well as the estimated disturbance is fed back to eliminate effectively the hysteresis between input voltage and output displacement of the PZT devices.

In this study, the dynamic characteristics of a turbine-meter-type flowmeter is investigated by making use of the remote instantaneous flow rate measurement method (RIFM). The results of the frequency response test indicated that the gain of the flow rate of the turbine-meter-type flowmeter relative to the flow rate of the RIFM was nearly unity up to 40Hz and the phase lag of the flow rate became 90 degrees at 70Hz.

The actuator saturation defects the countour control performance of mechatronics servo systems. In this paper, trajectory generation of contour control of the mechatronics servo system is developed taking into account of the constraints of the torque in the system. By using the generated trajectory, the torque constraint and assigned working accuracy are satisfied and the accurate contour control performance is achieved.

This paper presents a method of optimal design of an automatic transfer system which is controlled by the electro-pneumatic servo scheme. The electro-pneumatic automatic transfer system can move parts to desired points or displace defective parts. The dynamic performance of the system can be examined by observing the behavior of the output. The output of the servo control system is the motion of the cylinder, pneumatic actuator. The dynamic performance of the cylinder is governed by the parameters of the components of the entire system. The optimal design can be accomplished by selecting of the parameters such that the desired dynamic performance of the cylinder is obtained. The optimal set of parameters might be obtained through the repeated simulations. Repeated simulations, however, is not effective to determine the optimal set of parameters since the set of parameters is large. This paper presents modeling, application of an optimization method, and the numerical results. The optimization algorithm utilizes the concept of the conjugate gradient method. The results show that the suggested optimization scheme can render faster convergence of iteration compared to other method based on an algebraic optimization method and can reduce the design efforts.

A compliance control method of redundant manipulators is presented. This method is based on the new stiffness model, which allows us to modulate accurate joint stiffness of realizing the end effector stiffness to be varied with task requirements. Control model is developed and by implementing the proposed method in a three-dof(degree of freedom) planar redundant manipulator, its effectiveness is validated.

In this study, dynamic optimal design far a two degree-of-freedom anthropomorphic robot module is performed. Several dynamic design indices associated with the inertia matrix and the inertia power array are introduced. Analysis for the relationship between the dynamic parameters and the design indices shows that trade-offs exist between the isotropy and the dynamic design indices related to the actuator size. A composite design index is employed to deal with multi-criteria based design with different weighting factors, in a systematic manner. We demonstrate the fact that dynamic optimization is another significant step to enhance the system performances, followed by kinematic optimization.

This paper presents an impact control algorithm for reducing the potentially damaging effects by interation of redundant manipulators with their environments. In the. proposed control algorithm, the redundancy is resolved at the torque level by locally minimizing joint torque, subject to tire operational space dynamic formulation which maps tire joint torque set into the operational forces. For a given pre-impact velocity of the manipulator, the proposed approach is on generating joint space trajectories throughout the motion near the contact which instantaneously minimize the impulsive force which is a scalar function of manipulator's configurations. This is done by using the null space dynamics which does not affect the motion of an end-effector. The comparative evaluation of the proposed algorithm with a local torque optimization algorithm without reducing impact is performed by computer simulation. The simulation results illustrate the effectiveness of the algorithm in reducing both the effects of impact and large torque requirements.

Robot engineering is developed mainly in the field of intelligibility such as a manipulation. Considering the popularization of robots in the future, however, a robot should be studied from a viewpoint of saving energy because a robot is a kind of machine with a energy conversion. This paper deals with minimizing an energy consumption of a manipulator which is driven in a point-to-point control method. When a manipulator carries a heavy payload toward gravitation or the links are de-accelerated for positioning, the motors at joints generate electric energy. Since this energy can be regenerated to the source by using a chopper, the energy consumption of a manipulator is only heat loss by an electric and a frictional resistance of the motors. The minimization of the sum of these losses is reduced Lo a two-points boundary-value problem of an non-linear differential equation. The solutions are obtained by the generalized Newton-Raphson method in this paper. The energy consumption due to the optimum angular velocity patterns of two joints of a two-links manipulator is compared with conventional velocity patterns such as quadratic and trapezoid.

In the single sweep record of event-related potential (ERP), the peak latency of P300, which is one of the most prominent positive peaks in the ERP record, might fluctuate according to the recording conditions. The fluctuation of the peak latency (measurement fluctuation) is the summation of the fluctuation caused by physiological factor (physiological fluctuation) and one by noise of background EEG (noise fluctuation). We propsed a method for estimating the interval of the physiological fluctuation based on a limited number of single sweep records. The noise fluctuation was estimated by using the relationship between the signal-to-noise (SN) ratio and the noise fluctuation based on the P300 model and the background EEG model. The interval estimate of the physiological fluctuation were obtained by subtracting the interval estimate of the noise fluctuation from that of the measurement fluctuation. The proposed method was tested by using simulation data of ERP and applied to actual ERP and data of normal subjects, and gave satisfactory results.

A state or the arts in Japanese chemical process control is reviewed based on experience in applying advanced process control schemes to several industrial chemical processes. The applications validate model predictive control (MPC), the most popular advanced control scheme in the process control community, as, indeed, a powerful and practical control algorithm. However, at the same time, it is elucidated that MPC can solve only the control algorithm part of the problem and one needs chemical and systems engineering aspects to solve the entire problem. By illustrating several industrial process control problems, the need for chemical engineering aspects as well as the future direction for process control are addressed, especially in light or current attitudes toward product quality.

In this paper, we discuss a method for design of an ambulance stretcher which call decrease blood pressure fluctuation caused by ambulance acceleration. Recently, a lot of stretchers which can isolate the vertical vibration to reduce body resonances (4-10 Hz) have been used during ambulance transport. However, we have found that blood pressure of a patient laying in the stretcher fluctuates when the ambulance accelerates or decelerates. Since the enforced change of the blood pressure may deteriorate the patent's condition, a stretcher to cancel head-to-foot acceleration and to decrease the blood pressure variation (BPV) is expected for safe transport. We propose a method to design a stretcher which is tilted according to an adequate angle to cancel head-to-foot acceleration by gravity when the ambulance accelerates or decelerates. A control method of the stretcher is constructed by means of simulation analysis using acceleration data measured during ambulance transport. It is confirmed that the active controlled stretcher proposed has good performance for the BPV reduction.

We proposed a new variable sampling rate model which expresses the phenomena with both rapid and slow components. A method for determining the variable sampling rate and the older of the time series model was explained. The proposed variable sampling rate model was evaluated based oil an information criterion(AIC). Tile variable sampling rate model brought smaller an information criterion than one of a constant sampling rate model of conventional type, and was proved to be effective as a prediction model of the system with both rapid and slow components.

In this paper. we suggest new fuzzy modeling algorithm, which can be easily implemented, by combining HPC-MEANS Algorithm and Genetic Algorithm. HPC-MEANS used to cluster the sample data in input-output space will hyper planes and to make structure identification roughly and Genetic Algorithm is used to nine the premise and consequent parameters. For the validity of suggested methods we model the system with I/O data from known system. and then compare two systems.

In this paper, we discuss the modeling of flexible manipulators. In the modeling of flexible manipulators, there are two approaches: one is based on the distributed-parameter modeling and the other on the lumped-parameter modeling. The former has been applied to control and analysis of simple manipulator requiring precision, while the latter has been applied to multi-link spatial manipulator, because of the model's simplicity. We have already proposed the lumped-parameter modeling method for simple manipulator, and investigate that model of how much degree of precision we can get. The experiments and simulations are performed, comparing these results, the approximate performance of our modeling method is discussed.

This paper analyzes the dynamical modeling of high-rise building and the design of control systems for suppressing undesired vibrational motion at the top of the building originated by natural disturbances such as earthquakes, wind, etc. The control system is designed according to H$_{2}$ and H$_{\infty}$ robust control theories. The performance of the building with H$_{\infty}$ controller is analyzed in the time and frequency domains and the vibration isolation and robustness properties of H$_{\infty}$ and H$_{2}$ control systems are examined and compared. The design procedure, structure and properties of H$_{\infty}$ controllers are analyzed.zed.

Presented are closed-form expressions of the steady-state solution for the three-state exponentially correlated acceleration(ECA) target-tracking filter. The steady-state solution is derived based on Vaughan's approach for the case that the measurements of target position and velocity are available at discrete points in time. The solution for the ECA filter using only position measurements is obtained as a special case of the presented results.

In this paper the comparison between the neural networks and traditional approaches as system identification method are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. The examples considered do not represent any physical system, no a priori knowledge concerning their structure has been used in the identification process. Testing inputs for comparison are the sinusoidal, ramp and the noise ramp.

In this paper, we consider a problem to estimate process parameters using input-output data collected from the process operating in closed-loop control system. When orders and delay-time of the process are known correctly, under some conditions of identifying experiments, it is reported that accurate identification results can be obtained by applying prediction error method. To get accurate estimates, it is necessary to know orders and delay-time of the process. It is difficult to determine them in closed-loop identification, because ill-condition for identification are easily caused by selection of unsuitable order or delay time. Furthermore, the procedures to select orders and delay-time in open-loop identification aren't always available in closed-loop identification. The purpose of this paper is to determine a delay-time under suitable assumption that order of the process are known as the first step.

An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

An effective and disturbance suppressible controller can be obtained by assigning the left eigenstructure (eigenvalues/left eigenvectors) of a system. However, the disturbance decouplability is governed by the right eigenstructure(eigenvalues/right eigenvectors) of the system. In this paper, in order to obtain a disturbance decouplable as well as effective and disturbance suppressible controller, the concurrent assignment scheme of the left and right eigenstructure is proposed. The biorthogonality property between the left and right modal matrices of a system well as the relations between the achievable right modal matrix and states selection matrices are used to develop the scheme. The proposed concurrent eigenstructure assignment scheme guarantees that the desired eigenvalues are achieved exactly and the desired left and right eigenvectors are assigned to the best possible(achievable) sets of eigenvectors in the least square sense, respectively. A numerical example is presented to illustrate the usefulness of the proposed scheme.

This paper shows that the GPC with exponential weighting(GPCEW) can be applied to Electric furnace system which has large time delay. Stability of GPCEW can be guarantee from monotonically non-increasing property of Riccati difference equation. We show that the performance of GPCEW versus GPC and auto-tuning PID control is better than that of GPC or atito-tuning PID.

In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.

In this paper, an output feedback adaptive variable structure control scheme is presented for stabilization of large scale power systems. An additional input signal which is called a power system stabilizer(PSS) is needed to improve the stability of a power system and to maintain the synchronization of generators. The proposed PSS scheme does not require a priori knowledge of uncertainty bounds. It is guaranteed that the closed-loop system is globally uniformly ultimately bounded by the Lyapunov stability theory. Simulation results for a multimachine power system are given to show the feasibility of the proposed scheme and the superiority of the proposed PSS in comparison with the conventional lead-lag PSS of PID-type.

A passivity-based adaptive controller for robots executing fine motion tasks is proposed. The robot dynamics is modelled such that it is subject to holonomic constraints and hence it can be treated as a particular case of constrained motion tasks. Energy-motivated stability analysis is used to conclude the asymptotic stability. Remarks regarding the structure of the controller are given. A computer simulations study is presented and a robust constraint stabilization algorithm is also proposed.

Adaptive control systems based upon the command generator tracker(CGT) approach have attracted considerable interest because of the simple structure of its adaptive controller. Some attempts to such improve the adaptive control algorithm, for the sake of the application to broader class of plants, are made. Recently, Su and Sobel(1992) proposed that those schemes can be treated by an unified theory using a metasystem representation with some types of supplementary dynamics. However, in their method, it is difficult to find the dynamic compensator, which is proper and output feedback stabilizable, for the uncertain plant. This paper proposes a new design method of such supplementary dynamics and some parameters of adaptive control system for linear time invariant SISO plants. The method gives a concrete and systematic design method using only a few priori knowledge of the plant.

This paper presents a nonlinear adaptive control approach to a 4-point attraction magnetic levitation system using the local coordinates transformation and neural network. Based on local coordinates transformations, the magnetic levitation system can be represented in a state magnetic levitation system can be represented in a state space from of a 4-input 4-output. Neural networks which are defined in the new coordinates are used to learn the nonlinear functions of the system which are defined in the new coordinats also. The parameters of the neural networks are updated in an on-line manner according to an augmented tracking error. The simulation results are reported in this paper.

Mathematical model of the pollution rate of substation insulators is constructed, taking the model parameters as wind speed, wind direction, typhoon conditions and rainfall in an hourly basis. The main feature of model construction is to distinguish the effect of each parameter by separately analyzing the positive and negative pollution causing factors. Model parameters for the insulators of Karatsu substation, Saga, Japan were estimated and model validation was done using the actual data, in which the pollution deposits on the insulators were measured using pilot insulator and 'salt meter'. The proposed model of the pollution rate [mg/cm$^{2}$/hr] enables the identification of the effective parameters and prediction of the pollution rate so that it helps for the automatic decision making for insulator cleaning or the model can be used as a tool for the substation engineers to make precautionary measures.

A mathematical model is developed for a batch reactor in which the free radical bulk copolymerization of styrene and acrylonitrile takes place. In this model, we introduce the free volume theory to quantify the diffusion controlled termination and propagation reactions, and develop a model for the chain length dependent termination reaction in the context of the pseudo kinetic rate constant method(PKRCM). The simulation results from this model are found to be in good agreement with experimental data under different copolymerization conditions. The present model can predict both the copolymer composition and the number and weight average molecular weights. These kinetic approaches provide greater insight into the performance of the batch reactor used for the free radical bulk copolymerization of styrene and acrylonitirle.

The attitude stability of a satellite in spin-stabilized injection mode which contains a liquid pool is investigated. The satellite model for investigation is a two-body system consisting of a the main body, which is symmetric and rigid, representing the spacecraft, and a spherical pendulum, representing the liquid pool. Assuming that both spacecraft and pendulum are in states of steady spin about the symmetry axis of the spacecraft, the coupled nonlinear equations of motion for the system are simplified. In this paper, by using the multiple scales method, the possible resonance conditions in terms of the system parameters are determined and the corresponding near-resonant solutions are derived.

On the satellite communication system, conventional key issues of control have been focused on the attitude and orbit control, monitoring and control of communication payload such as IOT(In-Orbit-Test) and CSM(Communication System Monitoring) and so on. As the vulnerabilities are being increased on the satellite communication network, security services are required to protect it against security violated attacks. In this paper, a security architecture for satellite communication network is presented in order to provide security services and mechanisms. Authentication protocol and encryption scheme are also proposed for spacecraft command authentication and confidentiality.

This paper deals with a Batch processor application to determine orbit trajectories from satellite tracking data. The purpose of this paper is to find the initial state vectors. In order to determine the better estimation process, several different cases are compared. Here we adapt a minimum variance concept to develop estimation and prediction techniques. These results are compared with by SEP, Spherical Error Probable, values.

For the effective use of satellite communication transponder, tests for the payload system such as IOT(In-Orbit Test), RPM(Routine Payload Monitoring), CSM(Communicatios System Monitoring), and REV(Remote Earth-Station Verification) have to be conducted. Those tests are used in order to verify the condition and generic design of the satellite, to provide a database for operational calculations, and to maintain the quality of communication services. As the satellite communication system gets with wider expansion with higher complexity of operation, tests for the communication system also need more complex operation that usesophisticated computer-controlled measuring system. For and C language based measurement functions, which uses GPIB protocol and SCPI commands. But SICL requires knowledge of BASIC and C language as well as GPIB and SCPL system. This paper introduces a new language called CALSTEP-Control and Access Language for the Systems of Test Equipment and Payload. This language is designed for the operator to perform the tests for the satellite communication system without any special knowledge that is mentioned above. This language has very limited number of commands which are to be used to control the payload system and test equipments to perform IOT and CSM, and those commands are very readable and easy to understand, so an operator without any knowledge of BASIC and C programming language, or SICL and SCPI command can use it.

An extended study of optimal thruster combination for simultaneous attitude and orbital maneuvers of a jet-controled spacecraft is conducted. In this case, the spacecraft has not enough number of thrusters to control the rotation and translation separately. Therefore, thrusters are employed by combining to eliminate their coupling effects. The combinations are determined to minimize the fuel consumption. The redundancy study for some thruster failure cases is also presented.

Shuster's algorithm for spin-axis determination is extended to include sensor bias and mounting angle as its solve-for parameters. The relation between direct and derived measurements bias is obtained by linearizing their kinematic equations. A one-step least-square estimation technique referred to as the 'closed form' solution is used, and the solution provides a more refined and decent initial guess for the subsequent filtering process contained within the differential correction module. The modified algorithm is applied for attitude determination of a GEO communication satellite in transfer orbit, and its results are presented.

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

Integration of intelligent robot workcell is now a hot issue in CIM and robotics area. This piper dealt with relatively low-level essential topics, i.e., multi-robot coordination and real-time communication for the integration of intelligent robot workcell. For the coordination of multi-robot system, the tightly-coupled coordination is proposed using the various sensors. In order to handle the numerous communication data, time-critical communication network (Field-bus) is introduced and investigated. Finally, intelligent robot workcell is suggested using the Mini-MAP and Field-bus.

This paper describes an autotuning fuzzy PID controller for a position control of DC serve motor. Because ZNM(Ziegler-Nichols Method) with relay feedback has the difficulty in re-tuning the PID parameters and adaptive method has complex algorithm, a new method to overcome those problems is required. The proposed scheme determines the initial PID gains by using ZNM with relay feedback, and then re-tunes the optimal PID parameters by using fuzzy expert system whenever control conditions are changed. To show the validity of the proposed method, a position control of DC servo motor is illustrated by computer simulation and is experimented by a designed controller.

Recently, complicated and dexterous tasks with two or more arms are needed in ninny robot manipulator applications which can not be accomplished with one manipulator. In general, when two arms manipulate an object, tile dynamics of the arms and the object should be considered simultaneously. In order to control the force of tile arms, we can use various control schemes based upon dynamic modeling. But, there are difficulties in solving inverse dynamics equations, and the environment where a manipulator performs various tasks is usually unknown, and we can not describe a model precisely, for instances, the effect of the joint flexibility, and the friction between the arm and the object. Therefore, in this paper, we suggest a new force control method employing fuzzy inference without solving dynamic equations. Fuzzy inference rules and parameters are designed and adjusted with the automatic fuzzy modeling method using the Hough transform and gradient descent method.

To increase the robustness of tile feedforward tracking control system, a new discrete time sliding function has been defined and utilized for the formulation of control law, In adaptive case the robustness is achieved by using both a normalized gradient algorithm with deadzone and a sliding function-based nonlinear feedback, while in nonadaptive case by using only a sliding function-based nonlinear feedback.

In this paper we deal with a design of CCV adaptive flight control system having adaptive observer under the mircroburst circumstances. First, based on the observerbility indices of the controlled system, which is a general multi-variable one, the adaptive observer is constructed, and the unknown interactor matrix can be estimated by using the identified parameters. Next, CCV adaptive flight control law is calculated based upon the estimated ones. Finally, the proposed CCV adaptive flight controller is applied to STOL flying boat and numerical simulations under the microburst circumstances can be show to justify the proposed scheme.

Convergence of the state error e to zero in adaptive systems is shown using the uniqueness of solutions and the existence of a Lyapunov function in which the adaptation laws are constructed. Results in the paper are general, and therefore applicable to any adaptive control of a linear/nonlinear, time-varying or distributed-parameter system. Since the approach taken in the paper does not require the boundedness of the derivative of the state error e for all t .geq. 0, it is particularly useful in the adaptive control of infinite dimensional systems.

The adaptive control and the robust control have been considered as the most influential methods for robotic motion control. The purpose of this paper is to compare control performance between these two strategies in unconstrained motion control of robot manipulator. In order to compare control performance properly, intensive experiments are required and only then can conclusions be drawn on the relative merit and demerit of the controllers. Firstly, the control algorithms for unconstrained motion control are summarized. In adaptive control, the controllers that have been proposed so far are classified according to the signals used for the computed control input. It enables rather easier to compare controller is examined to demonstrate control performance of robust controllers. Finally, the above two approaches, the adaptive and the robust are compared from the view-point of robustness to plant uncertainty, which is one of the most demanding properties in robot motion control.

In this paper, the equations of motion are constructed systematically for multibody systems containing closed kinematic loops. For the displacement analysis of the closed loops, we introduce a new mixed coordinates by adding to the reference coordinates, relative coordinates corresponding to the degrees of freedom of the system. The mixed coordinates makes easy derive the explicit closed form solution. The explicit functional relationship expressed in closed form is of great advantages in system dimension reduction and no need of an iterative scheme for the displacement analysis. This forms of equation are built up in the general purpose computer program for the kinematic and dynamic analysis of multiboty systems.

A new approach to deal with the model matching problem for square plants is suggested. Admissibility conditions of the model matching error are derived in terms of state-space parameters and the derived formulas are exploited to obtain the solution to the model matching problem in H$_{2}$ norm.

This paper describes how to recognize hand written Hangeul character using the stroke order of the elementary segment. The recognition system is constructed of parts : character input part, segment disassembling part, character element extraction part and character recognition part. The character input part reads the character and performs thinning algorithm. In the segment disassembling part, the input character is disassembled into elementary segments using the direction codes and the feature parameters. In the character element extraction part, we extract the character element using the stroke order and the knowledge rule. Finally, we able to recognize the hand written Hangeul characters by assembling the character elements, in the character recognition part.

The authors have been devoted to researches on fuzzy theories and their applications, especially control theory and application problems, for recent years. In this paper, the authors present results on a comparison of optimal solutions between ones of an ordinary-typed mathematical linear programming problem(O.M.I.P. problem) and ones of a Zimmerman-typed fuzzy mathematical linear programming problem (F.M.L.P. problem), and comment about the sensitivity (differences and fuzziness on between O.M.L.P. problem and F.M.L.P. problem) on optimal solutions of these mathematical linear programming problems.

It is well known that the neural network can be used as an universal approximater for functions and functionals. But these theoretical results are just an existence theorem and do not lead to decide the suitable network structure. This doubfulness whether a certain network can approximate a given function or not, brings about serious stability problems when it is used to identify a system. To overcome the stability problem, We suggest successive identification and control scheme with supervisory controller which always assures the identification process within a basin of attraction of one stable equilibrium point regardless of fittness of the network.

In this paper, we discuss a design method of iterative learning control systems for parabolic linear distributed parameter systems(DPSs). First, we discuss some aspects of boundary control of the DPS, and then propose to employ the Karhunen-Loeve procedure to reduce the infinite dimensional problem to a low-order finite dimensional problem. An iterative learning control(ILC) for non-square transfer function matrix is introduced finally for the reduced order system.

In this paper, a new design method of variable structure model following control system(VSMFCS) for robot manipulators is proposed. The proposed controller overcomed reaching phase problem by using function augmenting scheme to the sliding surface. Therefore, it can be guaranteed that the overall system always has a robust property against parameter variations and external disturbances. Furthermore, the proposed controller does not use the model state, .chi.$_{m}$, different from other previous works. Regardless of not using the model state, the model following error dynamics, virtual dynamics, is shown to be globally exponentially stable. The efficiency of the proposed method has been demonstrated by an example.e.

This paper presents a real-time calculation method to generate the trajectory of robot manipulator for the purpose of avoiding collision. In order to model 3-D workspace, we use octree which has been used for fast collision detection. The levels of octree are used as the cost function to represent the distance between the manipulator and the obstacles. This criterion is not exact, but, due to this, we can obtain the approximate feasible trajectory extremely quickly. We will show the effectiveness of our method with some simulation examples. For example, the proposed method can solve a problem within 1 second on Intel 80486 processor running at 33 MHz. It has taken more than half an hour with one of the previously proposed methods.

In this work, we propose a planar three degree-of-freedom parallel mechanism as another type of assembly device which utilized joint compliances. These joint compliances can be adjusted either by properly replacing the joint compliances or by actively controlling stiffness at joints, in order to generate the desired operational compliance characteristics at RCC point, The operational compliance matrix for this mechanism is explicitly obtained by symbolic manipulation and its operational compliance characteristics are examined, it is found that the RCC point exists at the center of the workspace when the mechanism maintains symmetric configurations. Compliance characteristic and its sensitivity of this mechanism is analyzed with respect to the magnitude of the diagonal compliance components and two different matrix norms measuring compliance sensitivity. It is expected that the analysis results provide the designer with a helpful information to determine a set of optimal parameters of this RCC mechanism.

Dynamic hybrid position/force control of flexible manipulators is proposed. First, a 2 D.O.F. flexible manipulator is modeled using the spring-mass model. Second, the equation of motion considering the tip constraints is derived. Third, hybrid position/force control algorithm is derived. In this control algorithm, the differentiable order of the desired trajectory and the stability condition are different from the case of rigid manipulators. Lastly, to verify the effectiveness of the proposed control algorithm, simulation results are presented.

This paper is concerned with a motion control of a manipulator under parametric uncertainties and external disturbances. The parametric uncertainties are regarded as internally generated disturbances in the manipulator. Based on this idea, we formulate a model reference control problem with desired disturbance attenuation. The solution of this control problem not only reduces the worst-case effect on tracking error due to internal and external disturbances (combined disturbances) as much as possible, but also achieve optimal tracking when perturbations are absent. In order to solve the control problem which is formulated in this paper we reduce it to a constrained minmax cost control problem. A differential game theory is used to treat this constrained minmax cost control problem. The differential game theory leads to a sufficient condition for the global solvability of the model reference control problem with desired disturbance attenuation.

This paper presents a method to calculate the characteristic root areas and loci band of control systems with uncertainties. First, equations of boundary curves of root areas in the case of additive and multiplicative perturbation are derived. Then, an algorithm for the calculation of the array of closed curves is presented. When the upper bound of the absolute values of frequency responses for the uncertain part, is also frequency-dependent, the frequency-dependent, terms are included in the characteristic equation of the nominal system. This lead to the boundary equations of the root, areas for control systems with frequency-dependent uncertainty. Numerical examples of the control systems with multiplicative perturbations including frequency-dependent terms are presented to verify this calculation method. Finally, its applications to the design of robust control systems, e.g., passive adaptive control systems are also discussed.

This study is concerned with H$_{\infty}$ control theory of nonlinear systems. Recently H$_{\infty}$ control theory has been developed to nonlinear systems, and especially nonlinear H$_{\infty}$ control theory based on the Hamilton-Jacobi inequality has been proposed. This corresponds to linear H$_{\infty}$ control theory based on the Riccati equation. In this paper, we apply it to a semi-active dynamic vibration absorber for multi-degree-of-freedom structure, and we design its state feedback controller via the Riccati equation. In the simulation, we show that it is effective for a vibration control.rol.

In this paper the system called the inverse model compensation system is proposed as a system whose input-output transfer function can be regarded as that of a model with uncertainty in spite of including an unknown plant. And their to construct the robust model following system, which is of low sensitivity and robust stability, in order to control the inverse model compensation system is proposed. The simulation experiments show that the robust model following system including the inverse model compensation system is practical and useful as a system which controls unknown plants.

Algebraic matrix Riccati equations of the form, FP+PF$^{T}$ -PRP+Q=0. are analyzed with reference to the stability of closed-loop system F-PR. Here F, R and Q are n * n real matrices with R=R$^{T}$ and Q=Q$^{T}$ .geq.0 (nonnegative-definite). Such equations have been playing key roles in optimal control and filtering problems with R .geq. 0. and also in the solutions of in H$_{\infty}$ control problems with R taking the form R=H$_{1}$$^{T}$ H$_{1}$-H$_{2}$$^{T}$ H$_{2}$. In both cases an existence of stabilizing solution, i.e. the solution yielding asymptotically stable closed-loop system, is an important problem. First, we briefly review the typical results when R is of definite form, namely either R .geq. 0 as in LQG problems or R .leq. 0. They constitute two extrence cases of Riccati to the cases H$_{2}$=0 and H$_{1}$=0. Necessary and sufficient conditions are shown for the existence of nonnegative-definite or positive-definite stabilizing solution. Secondly, we focus our attention on more general case where R is only assumed to be symmetric, which obviously includes the case for H$_{\infty}$ control problems. Here, necessary conditions are established for the existence of nonnegative-definite or positive-definite stabilizing solutions. The results are established by employing consistently the so-called algebraic method based on an eigenvalue problem of a Hamiltonian matrix.x.ix.x.

In this paper, the robust stability of characteristic polynomials with respect to real parameter variations is investigated through a new functional approach. Specifically there is no restriction on the interrelationship between coefficients of the polynomials. This allows one to treat the robust stability problems alike without distinction as to continuous or discrete time systems. Necessary condition and sufficient condition for the robust stability are shown and some examples extracted from two-link planar manipulator are provided.

This paper is concerned with assess the possibility of robust pole assignment of proportional integral(PI) state feedback control system. First, the equivalence relations between a PI control system and an argumented control system proposed by Kawaji and Kim(1994) are extended from the new points of views of invariant closed loop poles. Second, on the relations, a remarkable result that the integral gain of PI control system is directly related to the insensitivity of system is presented. And, it is shown that the design of robust PI pole assignment is possible under the certain conditions.

In this paper, a fish-drying control method is proposed, which utilizes prediction of proper change in- weight of material fish based on skilled worker's performance. The function of the proposed system is largely broken down into two procedures: The procedure before drying and the one during drying. The procedure before drying is the determination of necessary drying conditions and the required drying time. Required drying time and proper changes in weight for a specific product are obtained by using fuzzy inference and regression models. The procedure during drying is the prediction of the state of material at the end of drying, or the state of product and regulation of drying conditions to attain the prescribed goal before drying. The prediction of product is obtained by using a set of linear-differential equations obtained by the authors' previous work. Drying conditions are regulated by using fuzzy inference. A good agreement between the results of simulation and experiments is obtained, which implies the usefulness of the present control method.

So far many researches have studied to control a cart system with a pole on the top of itself (forwards we call it simply a cart system) which is movable only to the directions to which a cart moves, using neural networks and genetic algorithms. Especially which it wag solved by genetic algorithms, it was possible to control a cart system more robustly than ordinary methods using neural networks but it had problems too, i.e., the control time to be achieved was short and the processing time for it was long. However we could control a cart system using standard genetic algorithm longer than ordinary neural network methods (for example error backpropagation) and could see that robust control was possible. Computer simulation was performed through the personal computer and the results showed the possibility of real time control because the cpu time which was occupied by processes was relatively short.

A elevator group supervisory system is designed to perform efficient operation of multiple elevators, and its basic function is to assign an appropriate elevator to a given hall-cell. In this paper, in order to improve elevator group control performance, we propose a new dispatching system which includes fuzzy multi-attribute decision making(MADM). In most cases, the purpose of group control is to maximize control goals as much as possible. Unfortunately, the decision of optimal elevator to a given hall cell is made with very uncertain information of the system, and some of control goals are related each other. The uncertainty is mainly resulted from car calls generated by serving hall calls. A fuzzy MADM algorithm is proposed to deal with these problems to improve system performance.

In a large class of industrial robot manipulators, its end effector for supporting the moving object have designed with mechanical suspension method(gripper). In this paper, We describe a high performance magnetically levitated end effector of robot, where is no mechanical contact and friction.

In this paper, we will investigate the position estimation problem for autonomous mobile robots. Formulating this as a state estimation problem for nonlinear SISO system, then we will apply several types of nonlinear observers. Simulation results of observer-based navigation control will be also provided.

The purpose of this paper is to present the details of design procedure of a nonlinear regulator by Riemannian geometric approach and to applied it to the case of a double-effect evaporator. A nonlinear geometric model is proposed on a direct sum space of a state vector and a control vector as well as in the previous parers by the authors. The geometric model is derived by replacing the orthogonal straight coordinate axes of a linear system on the direct sum space with the curvilinear coordinate axes. The integral manifold of the geometric model becomes homeomorphic to that of fictitious linear system. For the geometric model a nonlinear regulator with a performance index is designed renewedly by the procedure of optimization. The construction method of the curvilinear coordinate axes on which the nonlinear system behaves as a linear system is discussed. To apply the above regulator theory to double-effect evaporators especially to the pilot plant at the University of Alberta, a suitable nonlinear model is determined by the plant dynamics. The optimal control law is derived through the calculation of the homeomorphism. As a result it is confirmed that the regulator is effective and superior to that of the conventional control.

An adaptive learning control scheme by use of multilayer neural networks for compensating for uncertainties in nonlinear dynamic system is examined. Multilayer neural networks are introduced to map the uncertainties in nonlinear dynamics and perform nonlinear state feedback. Parameters of neural networks are adjusted by conventional back-propagation algorithms modified with the projection operation. Effectiveness of the proposed scheme for tracking control are demonstrated through computer simulations.

Electric Power system is a large scale nonlinear control one. Therefore, nonlinear control is desirable for the stabilizing, and it is thought that to establish an analytical method for optimal control inputs of AVR(automatic voltage regulator) and GOV(governor) is an important subject. In this paper, as a simple case, one-machine infinite-bus electric power model system with GOV is treated under the three kinds of control inputs; (i) fuzzy control input, (ii) linear control input and (iii) no control input. Next, the stability for each case is analyzed, and the three-dimensional stability regions and control responses are evaluated and compared. Finally, it is concluded that the linear control input does not necessarily give a good region and response, and the fuzzy one is better than others.

In this paper, we propose a new design approach of a two-degrees-of-freedom compensator which assures the robust stability. First of all, we clarify the internal structure of the generalized two-degrees-of-freedom compensator. By adopting this structure, we can make a bridge between the generalized controller and the disturbance observer based controller, Secondly, based on the clarified structure we derive a robust stability condition, and propose a design algorithm of free parameter taking the condition into account. The proposed design algorithm is easy to implement and, as a result, we obtain lower order free parameter then that of the conventional design algorithm.. Thirdly, we show by adopting an appropriate coprime factorization that the clarified structure can also be regarded as an extended version of the conventional PID compensator. Finally, we apply the proposed algorithm to a three-degrees-of freedom direct drive robot, and show some experimental results to verify the effectiveness of the proposed algorithm.

This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

Recently neural networks leave been proposed as new computational tools for solving constrained optimization problems because of its computational power. In this paper, the shortest path finding algorithm is proposed by rising a Hopfield type neural network. In order to design a Hopfield type neural network, an energy function must be defined at first. To obtain this energy function, the concept of a vector-represented network is introduced to describe the connected path. Through computer simulations, it will be shown that the proposed algorithm works very well in many cases. The local minima problem of a Hopfield type neural network is discussed.

An application of H$_{\infty}$ synthesis to contact control of a manipulator is suggested. Based on computed torque linearization of a manipulator, a target dynamics for contact motion control is defined and used as a reference model. The target dynamics relates position and force errors through free motion impedance and force error compensators. The H$_{\infty}$ control synthesis is adopted to find an optimum the compensator for position tied force control in various directions of the end-effector. The optimization is performed on the augmented criteria, which trades off the sensitivity function of the errors and the input load at the joints. A design example of the compensator is provided that meets the design specifications.s.

This paper proposes some dynamic navigation strategy for a mobile robot among multiple moving obstacles. The control force of the robot which consists of repulsive and attractive force is based on the artificial potential field. The artificial potential fields is derived with position or(and) velocities of the objects. The simulation results shows the properties of the proposed strategies.

This paper describes new PID control methods based on the fuzzy logic. PID gains are retuned after evaluating control performances of transient responses in terms of performance features. The retuning procedure is based on fuzzy rules and reasoning accumulated from the knowledge of experts on PID gain scheduling. For the case that the retuned PID gains result in worse CLDR (characteristics of load disturbance rejection) than the initial gains, an on-line tuning scheme of the set-point weighting parameter is, proposed. This is based on the fact that the set-point weighting method efficiently reduce either overshoot or undershoot without any degradation of CLDR. The set-point weighting parameter is adjusted at each sampling instant by the fuzzy rules and reasoning. As a result, better control performances were achived in comparison with die controllers tuned by the Z-N (Ziegler-Nichols) parameter tuning formula or by the fixed set-point weighting parameter.

This paper presents a simple methodology for reducing the order of H$_{\infty}$ controllers in the mixed sensitivity control problems. The key point of this methodology is to transform the generalized plant expression to new one, where the control object and the weighting functions for the sensitivity function may have some poles on the imaginary axis. So that, this methodology makes it possible to use the standard method to solve the general H$_{\infty}$ design problems about the mixed sensitivity problems, even for a servo system or a oscillatory system. We derive that the order of H$_{\infty}$ controllers designed by this methodology may be reduced to n$_{p}$ where n$_{p}$ is the order of the denominator of the control object. It is clear that n$_{p}$ is lower than n$_{p}$ + n$_{s}$, which is the order of H$_{\infty}$ controllers obtained by the ordinary H$_{\infty}$ design method up to now, where n$_{s}$ is the order of the denominator of the weighting function for sensitivity. Finally, a numerical example is given to illustrate the results..lts.ts..lts.lts.

This paper is concerned with the positioning control of a flexible arm system using H$_{\infty}$ control theory with optimum sensor location. Firstly, by virtue of the orthogonality of the flexible modes of the flexible arm a reduced order model of the tributed parameter system(DPS) representing the arm has formulated. The dynamical coupling between the flexible arm and DC motor has been considered to formulate an motor composite model. In order to achieve precise positioning with vibration attenuation, sensors have been optimally located. Finally, a robust H$_{\infty}$ controller was designed and the performance of the positioning system has been analyzed.d.

In this paper, we develop two sufficient conditions for Schur stability of convex combinations of discrete time polynomials. We give conditions under which Schur stability of the extremes implies Schur stability of the entire convex combination. These results are based on Bhattacharyya's result(1991), the AHMC theory in Barmish and Kang's paper (1993) and the bilinear transformation. Important applications of the results involves robust Schur stability of a feedback system having degenerate interval plants in an extreme point context.

In this paper a new controller is proposed which gives the resultant system the appointed input-output properties, low sensitivity and robust stability. The proposed controller consists of a reference model and a robust compensator. The reference model determines the input-output properties of the total system and is constructed by using the nominal model of the plant. We can design the reference model by applying design techniques which pay attention to steady robustness and no attention to sensitivity and robust stability, and need all state variables of the plant. The robust compensator is obtained as a solution of the mixed sensitivity problem in H infinity control theory. Therefore, low sensitivity and robust stability are guaranteed in the resultant system. The simulation experiments show that the proposed controller is effective and useful.

As the need for switchover to FA and for rationalization increases in the industrial world, educational courses in schools are more and more taking up the subjects of electronic machines, mechatronics and systems, etc., subjects which are a fusion of the previous subjects of electricity, electronics and machines. At our junior college, a control engineering course was inaugurated in 1974 prior to any other schools that offered such courses. As automation progressed, the use of industrial robots spread rapidly. The year of 1980 is regarded as the first year that the use of industrial robots become widespread. Responding to the current requests, a one-year research course was added to the control engineering course in 1983. Moreover, a robot engineering course was newly established in 1984, in which mechatronics and industrial robotics were instructed intensively in high efficiency. As a teaching aid, an air robot system which was based particularly on the FMS model and possessed pattern recognition capabilities was completed in 1982. This system has been used since then as the nucleus for hands-on training with robots and systems. As more and more intelligent machines and artificial intelligence become widespread in industry, these subjects are taking on greater importance and greater sophistication in the education offered by this department. Educational institutions are seeking to provide facilities and curricula which will meet the technological needs of this age. Our college is not an institution at the graduate school level, but rather a school which is at the more practical junior college level. An outline of the facilities introduced at our school is presented and the results of utilizing it in industrial robot engineering education is reported.

In this paper, we analize the effect of a steering water used in a unified phase I-phase II semi-infinite constrained optimization algorithm and present a new algorithm based on the facts that when the point x is far away from the feasible region where all the constraints are satisfied, reaching to the feasible region is more important than minimizing the cost function and that when the point x is near the region, it is more efficient to try to reach the feasible region and to minimize the cost function concurrently. Also, the angle between the search direction vector and the gradient of the cost function is considered when the steering parameter value is computed. Even though changing the steering parameter does not change the rate of convergence of the algorithm, we show through some examples that the proposed algorithm performs better than the other algorithms.

The global stability of model reference adaptive control system (MRACS) in the ideal case was resolved in the 1980's. Hoever the improvement of the transient, behaviour of MRACS has not been discussed sufficiently even in the ideal case. Only a few attempts have so far been made at the application of MRACS to the practical systems in contrast to the theoretical systematization. Therefore, when we consider the practical usage of MRACS it is necessary to develop an improved design scheme with respect to transient behaviour. In this paper, we propose two design schemes improving transient behaviour of MRACS by mollifying the input synthesis in the conventional design scheme of MRACS. We present a design scheme of MRACS in which we utilize the design approach of variable structure system(VSS). After describing the above design scheme, we also propose the improved design scheme in which we introduce the dead-zone decided by the magnitude of the output-error between the plant and the reference model. The effectiveness of the proposed two design schemes are shown through computer simulations. As the results, by using these methods, the convergence of the transient response is greatly improved in comparison with the conventional one.

We propose a novel velocity detection method of moving object based on a speckle pattern on the target surface using a self-mixing laser diode (SMLD). By this measurement, it was confirmed that the speckle signal has its waveform independent of the target velocity, and has its averaged frequency directly proportional to the target velocity. So it will be possible to detect the velocity of the target transversely translating against the laser light beam using a compact measuring system.

The paper demonstrates that holon networks can be used effectively for identification of nonlinear dynamical systems. The emphasis of the paper is on modeling of complicated systems which have a great deal of uncertainty and unknown interactions between their elements and parameters. The concept of applying a quantitative model building, for example, to environmental or ecological systems is not new. In a previous paper we presented a holon network model as an another alternative to quantitative modeling. Holon networks have a hierarchical construction where each level of hierarchy consists of networks with reciprocal actions among their elements. The networks are able to evolve by self-organizing their structure and adapt their parameters to environments. This was achieved by an autonomous decentralized adaptation algorithm. In this paper we propose a new emergent evolution algorithm. In this algorithm the initial holon networks consists of only a few elements and it grows gradually with each new observation in order to fit their function to the environment. Some examples show that this algorithm can lead to a network structure which has sufficient flexibility and adapts well to the environment.

To prevent the stable states from the complex dynamics, the global behavior of the overall system must be considered. Thus, indirect adaptive scheme might result in needless responses. Discrete-time variable structure controllers for a well-known logistic map are designed for two deferent sliding hyperplanes. Impulse disturbances are fully rejected by tile virtue of discrete-time variable structure control(DVSC). A numerical example is given to illustrate the effectless of the DVSC.

The control system of a precise positioning mechanism with resonance and Coulomb friction has been designed using H$_{\infty}$ control theory, and the control performance has been verified by computer simulation and experimental analysis. The DGKF type H$_{\infty}$ control theory with scalar weighting factors was utilized for designing the control system. The followings have been confirmed from the present study: (1) The system with H$_{\infty}$ control presents better convergence and stability than the system with conventional control (PI-notch filter control). (2) The H$_{\infty}$ control system have good robustness properties for a wide range of operating conditions in the presence of external disturbances such as Coulomb friction and changing mechanical resonant frequency.ncy.

Most of the theorems of nonlinear stability is based on the Lyapunov stability theory. The Lyapunov function method is most well-known and provides precise and rigorous theoretical backgrounds. However, the conventional approach to direct stability analysis has been performed without taking account of damping effects. For accurate stability analysis of nonlinear systems, the damping effects should be considered. This paper presents a new method to derive a group of Lyapunov functions to reflect the damping effects by considering the integral relationships of the system governing equations.

There are great needs for checking machine operation status precisely in the iron and steel plants. Rotating machines such as pumps, compressors, and motors are the most important objects in the plant maintenance. In this paper back-propagation neural network is utilized in diagnosing rotating machines. Like the finger print or the voice print of human, the abnormal vibrations due to axis misalignment, shaft bending, rotor unbalance, bolt loosening, and faults in gear and bearing have their own spectra. Like the pattern recognition technique, characteristic. feature vectors are obtained from the power spectra of vibration signals. Then we apply the characteristic feature vectors to a back propagation neural net for the weight training and pattern recognition.

A method for obtaining Volterra kernels of a nonlinear system by use of pseudorandom M-sequences and correlation technique, proposed by the authors in 1993, is further analysed and some applications for identifying nonlinear system having feedback loop are shown.

Wrapping machines in cigarette factories are equipped with indexing drive units with roller gear cam. At present there are no simple, visual, diagnostic techniques for predicting failure in these nits at an early stage. This paper proposes that failure could be predicted by using either a modified version of kurtosis, or the Wigner distribution method. The nonlinear vibration model proposed in this paper takes into consideration the play between the m and the cam follower, and precisely simulates the actual vibration. Statistics on the variance in play, obtained from the data on time history, call then be used to evaluate the effects of tile mage oil the cam and cam follower.

This paper gives a general survey of model-based fault detection and dignosis methods. Specific applications of these ideas to boiler systems will also be discussed. A novel aspect of the fault detection technique described here is that it explicitly accounts for the effects of using simplified models and errors from linearizing a nonlinear system at an operation point. Inclusion of these effects is shown to lead to novel fault detection procedures which outperform existing methods when applied to typical fault scenarios in boiler systems.

In this paper, the new approach and technique are introduced and derived from the original Lyapunov direct method which is used to decide the stability of system conveniently. This proposed technique modifies the formal concepts of the sufficient conditions of Lyapunov stability and is able to generate the methods for the robust design of control systems. Also, it applies to the dynamic systems with bounded perturbations and the results of the computer program using the new concept are compared with those of previous research papers and conventional Lyapunov direct method. It is possible to recognize the practical improvements of the estimation of robustness bounds of the systems.

The robust compensation controller, which has been proposed by one of the authors and is based on the fundamental principle of making the plant follow the reference model, consists of the reference model and the robust compensator. The reference model is constructed by using the nominal model of the plant and determines the input-output properties of the resultant system. The robust compensator is obtained as a solution of the mixed sensitivity problem in H infinity control theory. Therefore the resultant system is of low sensitivity and robust stability. In the case where uncertainty does not occur in the plant, the plant follows perfectly the reference model. Therefore, in the case where uncertainty occurs in the plant, we propose the system configuration which improves the following accuracy without replacing the 개bust compensator but by identifying, the plant and reconstructing the reference model.

We propose a design method that uses H$_{\infty}$ optimization method to suppress oscillation of a shaft between motor and load for high precision (0.001 % of reference input) position controls. PI speed control loop was introduced as a minor loop. Standard problem is used for the modeling of the system and Glover-Doyle's algorithm is used for the optimization in the H$_{\infty}$ space. Friction is considered to be an important factor that makes it difficult for the system to reach steady state in short time. In this paper, we propose a hybrid controller that includes PI speed feedback loop, which is expected to have a role to reject torque disturbance like friction.n.n.

In this paper, a memoryless H$_{\infty}$ controller for linear systems with state and input delays is presented. The proposed controller is a delay independent stabilizer which reduces the H$_{\infty}$ norm of the closed loop transfer function, from the disturbance to the controlled output, to a precribed level. The controller is obtained by solving a minimization problem involving linear matrix inequalities.s.

An automatic measuring system of three dimensional shape by a projection method with grating pattern from in optical spatial modulator has been developed. The characteristics of the system were studied. This system is composed of a projector, an optical spatial modulator, a CCD camera, and computer. A liquid crystal is used as the optical spatial modulator. The grating patterns that ire projected on the surface of the object are controlled by the computer connected with the optical spatial modulator. The projector patterns are measured by the CCD camera. The data are transferred to the computer. After a transformation into line data, the data are analyzed to obtain the coordinate of the surface of the object. This system has advantages as follows. (1) It is possible to capture the surface topography without any contact. (2) The time required for the measurements is shorter than the light-section method. (3) An optical spatial modulator using a liquid crystal is possible to control the grating patterns accurately by a computer. Surfaces of a plate and a cylinder were measured. The threshold level had an influence on the measurement. It was shown that this system has adequae accuracy in the measurements.

This paper presents in image-based visual servo control scheme for tracking a workpiece with a hand-eye coordinated robotic system using the fuzzy-neural-network. The goal is to control the relative position and orientation between the end-effector and a moving workpiece using a single camera mounted on the end-effector of robot manipulator. We developed a fuzzy-neural-network that consists of a network-model fuzzy system and supervised learning rules. Fuzzy-neural-network is applied to approximate the nonlinear mapping which transforms the features and theire change into the desired camera motion. In addition a control strategy for real-time relative motion control based on this approximation is presented. Computer simulation results are illustrated to show the effectiveness of the fuzzy-neural-network method for visual servoing of robot manipulator.

The automatic detection of artifacts and vigilance level as for pre-processing of the automatic EEG interpretation are discussed. The equations for detecting artifacts and vigilance level were determined such that they would conform to the procedures that an EEGer (one of the authors, H.S.) usually adopts for visual inspection of the actual EEG record. The automatic EEG interpretation was found to be improved by the newly developed pre-processing method even will artifact contamination or in drowsy condition of the subjects.

In this paper reconstructing the internal resistivity and relative permittivity distribution is discussed. The iterative reconstruction method based on Finite Element method and Newton method were used to reconstruct both of resistivity ind permittivity distribution. The Finite Element model of impedance distribution is built in complex field of resistivity and capacitive medium. The reconstruction results based on computer simulated data and experimental data are presented.

In this study, we have evaluated the effect of amplitude and frequency perturbation of EGG signal during single vowels associated with laryngeal pathology. The normal EGG signal is properly characterized by an autoregressive model which has the optimal order of ninth using the parametric method. This can be analyzed by determining the transfer function. Perturbations in the fundamental pitch and in the peak amplitude of EGG signal derived with a four-electrode system using the modulation/demodulation techniques were investigated for the purpose of developing a decision criteria for the laryngeal function identification.

To realize artificial device with sensing ability of the human skin, a mono-material tactile sensor with three sensing functions made of some elastic thin electro-conductive rubber sheet with eight latticed patch elements is proposed. This trial sensor provides the information of three kinds of model material characteristics such as thermal property, hardness property and the surface situation of materials by setting up three kinds of surface models as test materials. It can be finally expected to estimate unknown model materials by analyzing the data of the sensor.

When a force impulse acting on a massive and plex object is measured with a dynamometer, be resonant vibration of the measurement system often leads to serious inaccuracies. A more accurate measurement is obtained when the transfer function ,of the object-dynamometer system is used to compensate for the error in the dynamometer's output signal. The natural frequency and the damping coefficient of the transfer function are estimated by analyzing the waveform of the free damped vibration period after the loading of the force has ended. The residue of the system is determined such that the compensated force spectrum becomes smooth within a neighborhood of the natural frequency. The effectiveness of this signal processing method is experimentally tested on a hammer impulse, under the assumption that the hammer's high resonant frequency accurately models the problems encountered in force impact measurement. The compensation method is used to derive a improved estimate of the hammer impulse.

A Robot system to realize a painting using a writing brush is explained here. Based on the three-dimensional data about the target china, the movements of the writing brush is determined. The movement is realized by the movement of two robot manipulators which move coordinatedly. Experimental results reveals the applicability of one system.

This paper describes an effective method to estimate a position of an automous vehicle equipped with a single CCD-camera along indoor passageways. Using the sequential image data from the self-movement of the vehicle, the position is estimated by integrating the approximated motion parameters. The detection of the yaw angle that is one of the motion parameter is difficult in general, e.g. slip or error for noise, therefore the different detection is presented, which is, without shaft encoders, based on a projection function for 2D-image data and a cross-correlation function so as to be robust for noise. The approximated geometric function to estimate the position is used to reduce the computational effort. To verify the effectiveness of the method, the analysis and the computational results are shown through the simulations. Furthermore, the experimental results by using the test vehicle for the real indoor passageway are shown.

This paper discusses the solution to the precise positioning control problem applied to a simple model of a dual stage or redundant positioner. The dual stage actuator presented here uses a VCM(Voice Coil Motor) as a coarse actuator and a piezoelectric actuator as a fine actuator. By adopting controllers with two-degree-of-freedom and by optimizing H$_{2}$ faster precise tracking can be realized. Experimental and numerical results are presented to demonstrate the control effects.

In this paper, the sensitivity, linearity and temperature drift characteristics of various capacitive force sensors are evaluated and compared using new experimental methods. In particular, two designs were employed to reduce temperature drift. Both types of sensor use high-sensitivity Al coated PET film, and their externals are miniaturized. The first has a layered design consisting of two dielectric substances with different temperature characteristics. The prototype of this design had a temperature drift of only 0.1% of the sensor's capacity in the 20-80.deg. C range. The second type uses both a dummy sensor ind an active sensor with the same characteristics. The temperature drift of the prototype was one-fifth the temperature drift of a single sensor.

Neural Networks (henceforth NNs, with adjective "artificial" implied) has been used in the field of control however, has a long way to fit to its abilities. One of the best ways to aid it is "supporting it with the knowledge about the linear classical control theory". In this regard we hive developed two kinds of parametric activation function and then used them in both identification and control strategy. Then using a nonlinear tank system we are to test its capabilities. The simulation results for the identification phase is promising. phase is promising.

In this paper, we discuss an application of LTR techniques to integral controller design for discrete-time non-minimum phase plant models. It is shown that the feedback property obtained by enforcing the conventional LTR procedure can be achieved by the partial LTR technique. In addition, we point out that the partial LTR technique provides more design freedom in shaping a target feedback property.

A new Riemannian geometric model for the controlled plant is proposed by imbedding the control vector space in the state space, so as to reduce the dimension of the model. This geometric model is derived by replacing the orthogonal straight coordinate axes on the state space of a linear system with the curvilinear coordinate axes. Therefore the integral manifold of the geometric model becomes homeomorphic to that of fictitious linear system. For the lower dimensional Riemannian geometric model, a nonlinear optimal regulator with a quadratic form performance index which contains the Riemannian metric tensor is designed. Since the integral manifold of the nonlinear regulator is determined to be homeomorphic to that of the linear regulator, it is expected that the basic properties of the linear regulator such as feedback structure, stability and robustness are to be reflected in those of the nonlinear regulator. To apply the above regulator theory to a real nonlinear plant, it is discussed how to distort the curvilinear coordinate axes on which a nonlinear plant behaves as a linear system. Consequently, a partial differential equation with respect to the homeomorphism is derived. Finally, the computational algorithm for the nonlinear optimal regulator is discussed and a numerical example is shown.

This paper presents a CMAC network based controller on the basis of Lyapunov theory. CMAC network is employed to approximate and to compensate the uncertainties induced by inaccurate modelling of the system. For the improvement of robustness under the bounded disturbances and the approximation error of the CMAC, the adaptation scheme with a deadzone and an additional control input are developed.

The objectives of this work are to present the dynamic simulation strategy based on cluster-modular approach and to develop a prototype simulator. In addition, methods for the improvement of computational efficiency and applicability are studied. A process can be decomposed into several clusters which consist of strongly coupled units depending upon the process dynamics or topology. The combined approach of simultaneous and sequential simulation based on the cluster structure is implemented within the developed dynamic process simulator, MOSA(Multi Objective Simulation Architecture). Dynamic simulation for a utility plant is presented as a case study in order to prove the efficiency and flexibility of MOSA.

A method of trajectory error estimation of a hypersonic vehicle, by a covariance analysis technique is presented and discussed. The method itself is a wellkown technique, however, the thema has been rarely treated. As the importance is increasing, it is explained here and some of our newly deviced techniques are also presented.

In the previous paper, we presented a new guidance law for a missile during boost phase. Thus, this paper deals with the guidance law for a missile after the thrust cutoff against an accelerating and turning target. It is essentially based on the concept of proportional navigation. Some simulation studies were performed using a three dimensional mathematical model of an air-to-air missile and the effectiveness of the guidance law presented was shown.

This paper presents numerical analyses of the low speed yo-yo maneuver of an aircraft to determine controls of thrust, bank-angle and angle-of-attack in the subsonic region in terms of the optimal control theory. Minimum-time flight paths are numerically calculated to overtake an opponent aircraft flying in some steady-state level turnings under several assumptions: both of aircraft are point masses and maneuver in the 3-Dimensional space. Their weights are considered constant in the maneuver. As a result of the analyses, the effectiveness of the low speed yo-yo maneuver is shown.

In this paper we deal with a synthesis of flight control system via nonlinear model matching theory. First, the longitudinal and lateral-directional equations of aircraft motion an CCV mode are considered except the assumption "variations on steady straight flight due to disturbances are very small". Next, a design method of the dynamic model matching control system based on Hirschorn's Algorithm is proposed to the above nonlinear system. Finally, the proposed control system is applied to the small sized, high speed aircraft, T-2 on CCV mode and numerical simulations are shown to justify the proposed scheme.ed scheme.

Some extended results in the study of two-position alignment for strapdown inertial navigation system are presented. In [1], an observability analysis for two-position alignment was done by analytic rank test of the stripped observability matrix and numerical calculation of the error covariance propagation using ten-state error model. In this paper, it is done by an analytic approach which utilizes the nonsingular condition of the determinant of simplified stripped observability matrix and by numerical calculation of the error covariance propagation accomplished in more cases than [1], and the twelve-state error model including vertical channel is used instead of ten-state error model. In addition, it is confirmed that this approach more clearly produces the same result as shown in the original work in terms of complete observability and there exist some better two-position configurations than [1] using the twelve-state error model.

This paper presents a new algorithm to determine the receiver position in satellite navigation for GPS(Global Positioning System). The algorithm which based on vector analysis is able to obtain simultaneously the receiver position and the direction vector which is from the receiver position to a satellite. In its first calculation stage it, does riot require the complex initial value which is used in the previous works and affects the accuracy of the observed receiver position. Furthermore, the algorithm tells us whether a selected configuration among the visible satellites is good or poor for the accuracy. Comparing the algorithm with the previous method, the effectiveness of the algorithm is verified through the experimental simulations.

Three synchronic variables (Deviation Time, Fairness Time, Synchronic Time) are defined for Timed Place Petri Nets (TPPN). These parameters show the dependency between the firing of transition subsets in the time domain by different values. The approaches in this paper can be used to find synchronic relations in Stochastic Petri Nets. This paper presents how to decide the minimum resources required to a Flexible Manufacturing Cell using Synchronic Time concept.

LSM(Least-Squares Method) has inherent limitation that precise system identification over wide frequency band is difficult especially at low frequency hand. In this paper we propose to use decimation, a spectrum analysis method widely used in signal processing. The merits of decimation are the flexibility of selection of the frequency hand concerned and the function of LPF(Low Pass Filter). In this paper, frequency-domain is divided into separate frequency bands which will be combined into full frequency-domain by using MDM(Multiple Decimation Method). In this way, free selection of sampling frequency for each hand is possible and the low frequency oscillation modes of LSM are avoided.

We propose a method to reduce the marking expression about the places when we model a discrete-event system using the Petri net. The net with reduced marking expression has the same dynamic behavior as the original model. The number of the places can be reduced by the number of the resource places of the Petri net, and consequently the net can be significantly simplified, still preserving the dynamic properties of the net.

This paper illustrates a new learning control for robot manipulators using Lyapunov direct method. It has been shown that under the proposed learning control robot manipulators are always guaranteed to be asymptotically stable with respect to the number of trials. The proposed control is also robust in the sense that the exact knowledge of the nonlinear dynamics is not required except for bounding functions on the magnitude.

This paper proposes a method of learning control in DC servomotor using a neural network. First we estimate the pulse transfer function of the servo system with an unknown load, then we determine the best gains of I-PD control system using a neural network. Each time the load changes, its best gains of the I-PD control system is computed by the neural network. And the best gains and its pulse transfer function for the case are stored in the memory. According the increase of the set of gains and its pulse transfer function, the learning control system can afford the most suitable I-PD gains instantly.

A new flux observer based vector control system of an induction motor is constructed by using an observer in which the commanded stator currents are used to estimate the rotor flux. In this system, the flux observer is formulated by using a model of induction motor in a stationary coordinate system. By considering an observer of induction motor in a fixed co-ordinate system located on its secondary flux, a slip frequency controlled type of vector control system is also proposed. From these control schemes, the relation between the conventional slip frequency controlled type system and the observer based one is clarified. The steady-state error of the developed torque which is caused by the parameter change of induction motor is analyzed and discussed for the selection of observer gains. The poles of the observer error dynamics and those of the observer based vector control system are calculated analytically by neglecting the machine parameter change. In order to analyze the robust stability, a linear model of the observer based vector control system is proposed taking into account the machine parameter change. By using this model, the trajectories of the poles and zeros of the torque transfer function are computed and discussed. To test validity of the theoretical analysis, experiments are conducted by using a digital signal processor (TMS320C30) and a current controlled voltage source PWM inverter.

This paper proposes a method of suboptimal control for DC servomotor using a neural network. First we consider a nonlinear observer which is constructed by using an approximated linear dynamics of the nonlinear system and a, neural network. The reccurent neural network is used for the learning of the dynamical system. Next we consider the nonlinear observer. Then, we apply the observer output to nonlinear optimal regulator and confirm the effectiveness by applying the method to the inverse pendulum system.

This paper proposes a continuous hitting by a flexible link hammer. This hammer system is used only the first mode of vibration for a desired hitting. The input of the hammer driver for a continuous hitting is obtained from numerical solutions of two sets of non-linear simultaneous equations which satisfy the hitting conditions. Being too complicated, these numerical calculations are not useful for online processing. Therefore, the multi-layered neural networks are applied to the generation of the input patterns of the hammer driver. The trained network outputs agree well to the numerical solutions.

A sodium chloride crystallizer shows oscillatory and nonlinear characteristics under its nucleating and growing process. Because these characteristics vary with operational condition, we can't control the product crystal size exactly with a PID controller or a sequence controller. Then, we make a model with threefold neural networks for the laboratory equipment that is a jet mixing crystallizer. We try to control the product crystal size with its neuro-model, and we reach the conclusion that our neuro-model is applicable to the practical crystallizer.

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.

We show an application of a genetic algorithm to, control systems including neural networks. Genetic algorithms are getting more popular nowadays because of their simplicity and robustness. Genetic algorithms are global search techniques for optimization and many other problems. A feed-forward neural network which is widely used in control applications usually learns by error back propagation algorithm(EBP). But, when there exist certain constraints, EBP can not be applied. We apply a modified genetic algorithm to such a case. We show simulation examples of two cart-pole nonlinear systems: single pole and double pole.

In this paper we show the performance of neural Chandrasekhar filtering which is a special case for the new method of neural filtering using the artificial neural network systems developed recently for the filtering problems of linear and nonlinear, stationary and nonstationary stochastic signals. The neurofilter developed has either the finite impulse response(FIR) structure or the infinite impulse response(IIR) structure. The neurofilter differs from the conventional linear digital FIR and IIR filters because the artificial neural network system used in the neurofilter has nonlinear structure due to the sigmoid function. Numerical studies for the estimation of a second order Butterworth process are performed by changing the structures of the neurofilter in order to evaluate the performance indices under the changes of the output noises or disturbances. In the numerical studies both Chandrasekhar filtering estimates and true signals are used as the training signals for the neurofilter. The results obtained from the studies verified the capabilities which are essentially necessary for on-line filtering of various stochastic signals.

Ussing's flux ratio theorem (1978) reflects a reciprocal relationship behavior between the unidirectional fluxes in asymmetric steady diffusion-convection in a membrane slab. This surprising result has led to many subsequent studies in a wide range of applications, in particular involving linear models of time dependent problems in biology and physiology. Ussing's theorem and its extensions are inherently linear in character. It is of considerable interest to ask to what extent these results apply, if at all, in situations involving, for example, nonlinear reaction. A physiologically interesting situation has been considered by Weisiger et at. (1989, 1991, 1992) and by McNabb et al. (1990, 1991) who studied the role of albumin in the transport of ligands across aqueous diffusion barriers in a liver membrane slab. The results are that there exist reciprocal relationships between unidirectional fluxes in the steady state, although albumin is chemically interacting in a nonlinear way of the diffusion processes. However, the results do not hold in general at early times. Since this type of study first started, it has been speculated about when and how the Ussing's flux ratio theorem fails in a general diffusion-convection-reaction system. In this paper we discuss the validity of Ussing-type theorems in time-dependent situations, and consider the limiting time behavior of a general nonlinear diffusion system with interaction.

In control system design, whether the various subsystems are in discrete time or continuous time, the state space is usually regarded as a continuum. However, when the system is implemented, some subsystems may have a state space which is a subset of finite computer arithmetic. This is an important concern if a subsystem has chaotic behaviour, because it is theoretically possible for rich and varied motions in a continuum to collapse to trivial and degenerate behaviour in a finite and discrete state space [5]. This paper discusses new ways to describe these effects and reports on computer experiments which document and illustrate such collapsing behaviour.

Complicated dynamical behavior can occur in model reference adaptive control systems when two external sinusoidal signals are introduced although the plant and reference model are stable linear first older systems. The phase portrait plot and the power spectral analysis indicate chaotic behavior. In the system treated, a positive Lyapuniov exponent and non-integer dimension clearly manifest chaotic nature of the system.

A hierarchical Petri- net is utilized in supervising an automated vehicle system, The supervisory system is supported by computer networking in order to facilitate necessary processing, and consists of control flow level and computer allocation level so that a designer and an operator can easily build and/or access to each level. There are two modes of utilizing Petri net here in this paper. One is to employ it in designing the control system, in order to optimally allocate computers in every stage of processing. The other is for supervision of the system in operation, in order for the operator to be in a easy-to-comprehend environment of operation. The effect of these two modes of utilizing Petri net is examined.