We present a hybrid self-tuning method using hyper elliptic Gaussian membership function. The proposed method applies a GA to identify the structure and the parameters of a fuzzy inference system. The parameters obtained by a GA, however, are near optimal solutions. So we solve this problem through a backpropagation-type gradient method. It is called GA hybrid self-tuning method in this paper. We provide a numerical example to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

Back-propagation is one of the efficient algorithms used to nonlinear optimizations or controls. In spite of its structual simplicity and learning ability, learning time is very long or bad case converge local minimum on complicate input patterns. In order to improve these matters varing learning rate and momentums were proposed. In this paper, to improve its performance fuzzy is adjusted in parameters, learning rate and momentums. Parameters are adjusted by errors and change of errors adaptively. In order to evaluate proposed method simulated with MATLAB on inverted pendulum.

Error-backpropagation has been used in the bulk of Practical applications for neural networks. While an emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. There is, however, no concrete theoretical results about the structure of a plant and the structure of a multilayered neural network and the learning rate. The paper investigates the relation between structure of a plant and a multilayered network and learning rate. Simulation study shows that the plant signal with a short period and a fast sam time is preferable for learning of the network emulator.

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

This paper describes RBF network controller based on fuzzy control rules for intelligent control of nonlinear systems. The proposed scheme is derived from the functional equivalence between RBF networks and fuzzy inference systems. The design procedure of the proposed scheme is realized by first transforming the fuzzy control rules into the parameters of RBF networks. The optimized RBF network controller is then performed through the gradient descent learning mechanism to an error function. The proposed method is rigorously tested using a nonlinear and unstable nonlinear system. Simulation is performed to demonstrate the feasibility and effectiveness of the proposed scheme.

This paper presents an Orthogonal Neural Network based on orthogonal functions and applies the network to nonlinear system control. The Orthogonal Neural Network doesn't have the problems of traditional feedforward neural networks such as the determination of initial weights and the numbers of layers and processing elements. In this paper, Orthogonal Neural Network is modified already introduced one by input transformation. The results show that the modified neural network has the better performance than existing one and performance of controller using this network is good.

This paper investigates the direct and adaptive control of mechatronic servo systems using modified chaotic neural networks (CNNs). For the performance evaluation of the proposed neural networks, we simulate the trajectory control of the X-Y table with direct control strategies. The CNN based controller demonstrates accurate tracking of the planned path and also shows superior performance on convergence and final error comparing with recurrent neural network(RNN) controller.

In this paper, a navigation system based on fuzzy logic controllers is developed for a mobile robot in an unknown environment. The structure of this fuzzy navigation system features sensor system, fuzzy controllers for motion planning and the motion control system for real-time execution.

This paper presents the new method of a nondestructive spot welding state inspection system using neural networks. The learning process of neural networks makes the inspection system to adapt the variable welding parameters. The inspecting process is working with on-line real-time after off-line learning process. This neural network based inspection system shows reliable results through the field test for variations of applied voltages, currents, and contact area of the welding electrode.

In linear motor positioning systems, nonlinearitys such as friction and cogging exist. These inner system with compliance may cause the steady state error and oscillation. So it is necessary to consider these elements for precision positioning control. In this paper, a nonlinear model of a linear motor positioning system including the friction, cogging and compliance is proposed. The parameters of the proposed model are identified by recursive least-squares method. The validity of the proposed model is confirmed by computer simulation.

We propose a decentralized $H_{\infty}$ state estimation method in the multisensor state estimation problem. The proposed method bounds the maximum energy gain from unknown external disturbances to the estimation errors in the suboptimal case. And we formulate the decentralized state estimation method in the general case of different global and local models using alternative gain equation of the $H_{\infty}$ state estimator which can calculate global state estimates from the the linear combination of local state estimates. In addition, the proposed update equation between global and local Riccati solutions can reduce unnecessary calculation burden efficiently.

A control synthesis scheme is presented for nonlinear single-input-single-output (SISO) systems with parametric uncertainty which have completely unstable zero dynamics. The approach involves the derivation of an input-output linearizing control law which achieves internal stability for a nonlinear minimum phase approximation to the original system using Fliess normal form. A vector of unknown constant parameters is also considered. A Lyapunov-based additional control law is shown to stabilize the full system.

In this paper, we characterize the whole class of vector fields that can be linearized by a given nominal state transformation and a feedback linearizing controller. The necessary and sufficient condition for a given uncertain vector field to be so-called "completely linearizable by the nominal coordinate transformation" is given in terms of Lie Bracket of uncertain vector fields and some suitable vector fields of the nominal system.

In this paper, a new approach to modeling and control of nonlinear systems using fuzzy theory is presented. To express the various and complex behavior of nonlinear system, we combine multiple model method with hierachical prioritized structure. The mountain clustering technique is used in partitioning of system, and TSK rule structure is adopted to form the fuzzy rules. Also we soften the paradigm of Mamdani's inference mechanism by using Yager's S-OWA operators.

An LQG/LTR based gain scheduling control scheme for the two link inverted pendulum is presented. It is shown by simulation that the gain scheduling scheme based on the robust linear control theory still preserves the robust property of the linear control scheme and can be applied to control a class of nonlinear systems.

In this paper, we consider the robust pole assignment inside the circular region for linear systems with time-varing uncertainty. The considered uncertainties are the norm bounded uncertainty and the matrix polytopes type uncertainty. Since the considered uncertainties are time-varying, it should remind that the closed loop system be time-varing system. Therefore, we should consider not only the pole assignment but also the stability. We present new conditions that guarantee the robust pole assignment and the robust stability. Finally, we show the usefulness of our results by an example.

본 연구에서는 저속에서 발생하는 측정잡음에 대한 문제를 불규칙 확률시스템으로 고려하여 Kalman 필터를 관측자로서 사용하고 고속에서뿐만 아니라 저속에서의 위치와 속도 추정성능을 향상시키고자 한다. Kalman 필터는 확률적 외란을 포함하고 있는 동적시스템에 적용되는 최적상태 추정자이다. 또한 이 Kalman 필터는 외란을 가지는 이산형 실시간 동적 처리 시스템에서 최적의 미지 상태를 추정하기 위해 선형, 불편향, 그리고 최소 오차분산 회귀형 알고리즘을 제공한다. 또한, MRAS(Model Reference Adaptive System) 방법을 이용하여 모터와 부하에 대응되는 기계적 시정수를 동정한다. 이 방법은 기계적인 시정수가 알려지지 않은 시스템에 적용하여 위치와 속도의 추정을 가능하게 하기 위해서이다. 더욱이 동정의 결과를 이용하여 Kalman 필터 알고리즘에 적용한다.

제어공학에서 흔히 표준 모델이라고 불리우는 플랜트 모델은 여러 부 시스템이 서로 결합되어있는 복잡한 시스템을 단순화시킨 모델이다. 이 모델은 수학적으로 간략하게 표시된다는 장점 때문에 다변수 시스템의 최적 제어에 많이 쓰이고 있다. 그러나 이 모델은 수학적인 전개에는 편리하지만 물리적으로 판이하게 다른 신호군 즉, 외란 및 측정 잡음과 기준 입력 신호를 하나의 신호군으로 처리하는 약점이 있다. 실제로 이 구조로는 입력 추종 문제를 자유롭게 처리할 수 없는 경우가 있다. 본 연구에서는 이러한 문제를 개선하기 위하여 외란 및 측정 잡음과 기준 입력을 분리하여 처리할 수 있는 2자유도 제어기 구조를 제시하였다. 제어기 형태는 위너-호프 제어기로 주파수 영역에서 다 변수 시스템에 대한 최적 설계를 가능하게 한다.

In this paper, we suggest a design scheme of receding horizon predictive control(RHPC) for boiler-turbine systems whose dynamics are given in nonlinear equations. RHPC is designed for linear state space models which are obtained at a nominal operating point of the boiler-turbine system. In this consideration, the boiler is operated in a sliding pressure mode, in which the reference value of drum pressure is changing according to the electrical power generation. The reference values of the system outputs are prefiltered before they are fed to the RHPC in order to compensate the linearization errors. Simulation results show that the proposed controller provides acceptable performances in both of the cases of 'steep and small changes' and 'slow and large changes' of power demand and yields the effect of modest coordination of conventional PID schemes such as boiler-following and turbine-following control.

The aim of this paper is to introduce a method designing the optimal model following boiler-turbine control system using genetic algorithms. This boiler-turbine control system is designed by applying genetic algorithms with reference model to the optimal determination of weighting matrices Q, R that are given by LQ regulator problem. These weighting matrices are optimized simultaneously in the search domain selected adequately. The effectiveness of this boiler-turbine control system is verified by computer simulation.

In this paper, A continuous control reaching law for variable structure control is proposed to reduce the chattering and improve the robustness properties in the presence of matched uncertainly.

It is well known that Variable Structure Controller(VSC) is robust to parameters variation and disturbance but its performance depends on the design parameters such as switching gain and slope of sliding surface. This paper proposes a more robust VSC that is composed of local VSC's. Each local VSC considers the local system dynamics which has narrow parameter variation and disturbance. We optimize the local VSC's by use of Evolution Strategy, and then we use Artificial Neural Network to generalize the local VSC's and construct the overall VSC in order to cover the whole range of parameter variation and disturbance. Simulation on BLDC motor current control has verified the proposed VSC is superior to the conventional VSC.

본 논문에서는 플랜트의 계측신호들에 나타나는 현상적인 특징파형들을 감지하여 플랜트의 고장을 진단하는 기법을 제시하고, 플랜트의 고장시 나타나는 여러 특징 파형들의 전형인 oscillatory 파형을 감지하는 알고리즘을 prediction filtering 기법을 적용하여 얻는 과정을 기술하였다. 또한 이의 구체적 적용 예로 500MW급 화력발전소의 보일러 제어 시스템을 대상으로 여러 고장상황에 대한 고장감지 알고리즘을 설계하였고 제시한 기법의 유용성을 보이기 위한 시뮬레이션 적용 결과를 보였다.

This paper describes a simulation method of the correlation-signal output, which has Doppler effect (variation of amplitude, phase, and frequency) caused by the moving-effect of target and encounter conditions. Using these results, we can develope and verify the algorithm of the signal processing parts of the code correlation range sensor with ease.

In this paper we propose a new RF range measurement method. Using two codes which have different chip rate, we transmit one code toward the direction of targets and calculate the distance by comparing it with the other untransmitted reference code. Because the measuring process is fully digitalized, the stability, resolution, flexibility, and compactness of the system are good. Some experimental results are provided to show the validity and the performance of the proposed method.

The CD Trend Recorder, developed as a substitution of the existing SCR (Stript Chart Recorder), acquires various outputs (e.g. frequency voltage, current, power, temperature, pressure, etc) simultaneously using PC up to 32 different outputs, display, and analyze them just like the existing SCR. It stores the data in CD-ROM so th various data can be stored permanently this system has built-in MMI program and to monitor and analyze the data in real-t expert system link the data to the do where needs the data to display, analyze, in the new medium at the same time.

This paper presents an estimation method of the number of partial discharge(PD) sources and their locations in power transformer. To identify multiple PD sources and their locations, the directions-of-arrival estimation algorithm is employed. The results of simulations shows that the proposed method could be accurately detect the number of PD sources and their locations in power transformer.

In this paper, We propose a variable structure controller with time varying switching surface. We calculate the maximum value of switching surface gradient under the bound of input. To enhance the robustness, we, choose a time varying switching surface gradient that is of the 3rd order polynominal form. We use evolution strategy to optimize the parameters of the switching surface gradient. Finally, the proposed method is applied to the motor position control. Simulation results show that the proposed method is more useful than the conventional variable structure controller.

In this paper, an efficient attitude determination algorithm based on the Kalman Filter which combines earth/sun sensor data with gyro data in a mutually compensating manner is presented. Quaternion is used as the attitude state to save computation time and to prevent the gimbal-lock situation associated with Euler angles. Gyro data allows the use of the kinematic equation instead of space vehicle's dynamic equation which is usually based on approximation of the actual dynamics and inaccurate torque information. The gyro data are used to propagate the attitude through kinematic equation and the earth/sun sensor data are used to update the attitude and estimate the gyro bias. Simulation results for the KOMPSAT attitude determination system are presented.

Hadamard Transform Spectrometer (HTS) is an instrument which measures the spectrum of a source with high signal to noise ratio using multiplexing advantage. While the conventional HTS has the 1-dimensional characteristics because it measures only the spectrum, the system presented in this paper is 2-dimensional so that it can measure the spectrum of each position. We introduce here 2-dimensional Hadamard transform spectrometer and analyze it. The $T^{-1}$ method which recover the spectrum and compensate the transmissive nonideality of the stationary electro-optical mask(EOM) are applied to the system. By computer simulations we show we can get better estimates from the proposed system than that from the conventional HTS.

This paper studies on a feedback active noise control method for the quasi stationary. The quasi one dimension space means a duct space which have a shorter 2th path than the one dimension space. To control noise signal, a feedback active noise control using FXLMS algorithm is used Computer simulation show that the algorithm can control noise signal in the quasi stationary.

Schemes for detecting and diagnosing faults are presented. Faults are detected when residuals change significantly and thresholds are exceed. Two stage artificial neural networks are applied to diagnose faults. The idealized steady state patterns of residuals are defined and learned by ANNs using back propagation algorithm. The first stage ANN is trained to classify the subsystem in which the various faults are located. The first stage ANN could be also used to detect faults with threshold, checking. The second stage ANNs are trained to discriminate the specific cause of a fault at the subsystem level.

This study is focused on the design and performance test of shaking table using stepping motor. Stepping motor can control the motion accurately with generated pulses and is applied to the shaking table. Earthquakes like El Centro and Taft are used as inputs to the shaking table. First, the number of pulses are calculated and sent to pulse generator. Then, the generator controls the table according to the pulse signs. It is shown that the measured signals from the table are in very good agreement with input signals of scale-downed earthquakes of El Centro and Taft. This table will be used for the experimental study of small-scaled building structures with tuned mass dampers under earthquakes.

In this paper, we suppose a fuzzy logic controller for cruise control of vehicle. Generally, fuzzy logic controller is known as a controller which can be coped with a non-linear and a complex system. The proposed fuzzy logic controller consists of three input variables; that is, a desired speed, a current vehicle speed, and a current acceleration, and one output variable, throttle angle. The supposed fuzzy logic controller is for engine speed control system is implemented on 80586 microprocessor with DT-2801.

In order to enhance the driveability of multi-wheel-drive electric vehicle fitted with a traction control system a traction control algorithm is proposed. Numerical computations show that the driveability could be considerably enhanced with respect to that of equivalent torque distribution vehicle.

In this paper, we present a fuzzy ICC using a self-tuning method. To provide robustness and adaptiveness over the vehicle nonlinearities and changes of the driving environments, an on-line self-tuning scheme based on 'Interior Penalty Function' was developed. Road test and computer simulation results verify the feasible performance of the suggested ICC algorithm.

The steer-by-wire (SBW) system has nonlinear dynamics inherently. In classical approach, the controller has been designed on a linearized model which corresponds to only an operating point. In this paper, a set of linearized model that is generated at different operating ranges is replaced by a linear transfer function having parametric uncertainty. Then a design method for robust control using QFT is represented. The Kharitonov like analyses shows that the proposed controller satisfies the given robust performance specifications well.

One of the most difficult tasks in the process of car license plate is the extraction of each character from within license plate region. This paper presents a real-time recognition of car licence number using neural network in parking lot. The feature parameters of letters and numbers of license plate are extracted by thinning algorithm. Both feature parameters are used to train neural networks for the image recognition.

Measurement errors in a temperature measurement system are mainly due to the consisting elements' accuracies and the circuit parameters' changes following the environment variations such as temperature. Further, system's non-linearity makes the measurement accuracy worse, and accordingly a linearization method should be considered to avoid this worsening. In this study, an error-correction method and a linearization method are proposed and a system utilizing these methods is realized.

The main purpose of this study was to develope the prototypes of on-line supervision system for maintenance to protect the confidence of operation of electric facilities in buildings. The influence of the harmonics on the electric facilities in building, which is recently growing more and more serious, were also analysed, and finally the essential techniques on the condition supervision, diagnosing method of facilities were proposed.

수차발전기 유지관리상 중요한 자료인 소음 진동을 주기적으로 측정하고 있는데 측정자의 전문성, 측정장비, 데이터 취득분석 등에 있어 일관성이 결여되어 과거 데이터를 현재 취득 값과 비교분석 할 수 없게 되었다. 그래서 수차발전기의 진동원인, 측정상의 주의점, 진동의 판정법, 수차발전기 이론진동수 조사, FFT Analyzer를 이용한 데이터분석의 실례를 보임으로서 보다 과학적인 설비관리의 기법을 보였다.

With Extraction Transient Data from Booster Pump System, This paper establishs system model equation. and This equation is capable of PID control. Using Ziegler-Nichole tunning method of PID, Constantly estimated control method is done.

We have developed a part of hydraulic stroke sensing cylinder using magnetic sensor that can detect each position under severe construction fields. In this paper, for evaluating the developed cylinder under various environment condition, temperature control systems and two hydraulic systems to be coupled consist of. The results show that the developed cylinder has good performance under the various environment condition.

In this paper, a system to control feeding rate by fuzzy controller was developed and tested in the various raw material of the powder gram state. The designed fuzzy controller for feeding rate control system is proved robust performance under parameter variation and load disturbance effect which is caused by the kind and quantity of various raw material.

In this paper, a transmitter and a receiver using two identical Chua's circuits are proposed and a wire secure communications are investigated. A secure communication method in which the desired information signal is synthesized with the chaos signal created by the Chua's circuit is proposed and information signal is demodulated also using the Chua's circuit. The proposed method is synthesizing the desired information with the chaos circuit by adding the information signal to the chaos signal in the wire transmission system. After transmitting the synthesized signal through the wire transmission system, it is confirmed the feasibility of the secure communication from result of demodulated signals and recovered wire tapped signals.

Chua's circuit is a simple electronic network which exhibits a variety of bifurcation and attractors. The circuit consists of two capacitors, an inductor, a linear resistor, and a nonlinear resistor. In this paper we analyze a circuit obtained by replacing the parallel LC resonator in the Chua's circuit by lossless transmission line. By using the method of characteristics of this circuit we show that various periodic motions and chaotic motions can the attained according to parameter variations. From Chua's circuit with a lossless transmission line, a variety of chaotic attractors which are similar to those of the normal Chua's circuit are observed.

In this paper, a sliding mode control-based fuzzy controller is suggested. It is a robust control method and can be applied in the presence of model uncertainties and parameter disturbances. An inverted pendulum is effectively controlled by the proposed method in spite of existing model uncertanties and parameter disturbances.

Fuzzy controller design consists of intuition, and any other information about how to control system, into a set of rules. These rules can then be applied to the system. If the rules adequately control the system, the design work is done well. If the rules are inadequate, the designer must modify the rules. Through this procedure, the system can be controlled. In this paper, we design fuzzy controller composed of two parts, one is balancing controller, the other is angle controller.

The analysis of distribution line faults is essential to the proper protections in the power system. A high impedance fault does not make enough current to cause conventional protective devices. In this paper, Fractal dimensions are estimated for distinction between normal status and fault status in the power system. Application of the concepts of the fractal geometry to analyze chaotic properties of high impedance fault current was described. In addition, to analyze variation of fault current and normal current on phase plane, embedding state variables are reconstructed from 1 dimensional time series.

일반적으로 pH제어계통의 특성은 반응시간이 길어 그 응답속도가 매우 느리게 된다. 따라서 기존의 pH 제어 계통에 P나 PI제어기를 이용하는 경우는 정밀한 제어가 될 수 없다. 본 논문에는 이러한 단점을 보완하기 위해 신경망이나 퍼지와 같은 지능제어의 적용 가능성을 고찰하기 위해 pH 제어계통에 기존의 고전적인 제어알고리즘과 지능제어 알고리즘을 적용하여 비교 검토하였다. 그 비교결과 지능제어 적용이 가능함을 입증 할 수 있었다.

원자력 발전소용 증기발생기의 수위제어에 기존의 경우 주로 PI 제어기를 이용하는데 반해 본 논문에서는 주급 수유량에 대한 주증기 유량의 변화를 신경망을 이용해 학습함으로서 PI제어기의 각 파라메터를 뉴닝하는 문제를 연구하였다. 적용하여 고찰한 결과 기존의 PI 제어기에 비해 수위변화에 대한 추종성능이 우수함을 나타내었다.

It is important to select a reliable electronic control system in power plants because a trip of a power plant caused by malfunction of the control system can lead to a great deal of economic and social loss. In this paper. environmental test specifications for evaluating the reliability of the electronic control system were developed in order to select a reliable one. Also, the electronic control systems made by domestic manufacturers were tested based on these developed environmental test specifications.

3차원 디스플레이에 있어서 여러 사람이 동시에 입체감 있게 3차원 영상을 볼 수 있게 하는 문제와, 관찰자가 움직이더라도 그 위치 변화를 추적하여 그에 따른 입체 영상의 변화를 반영함으로써 계속 양질의 3차원 영상을 볼 수 있도록 하는 문제들은 앞으로 해결해야 할 어려운 문제로 남아 있다. 본 논문에서는 이러한 문제들을 해결할 수 있는 방법을 제시하고 그에 따른 문제점 등을 살펴본다.

실제 디젤 자동차를 운행할 때 헌팅이나 서지현상이 발생하여 운전상 좋지 못한 현상이 발생한다. 자동차의 디젤기관은 회전수의 안정화를 도모하기 위해서 연료 분사펌퍼의 분사량 조정봉(Rack)을 가바나의 조속기에 의해 위치 제어할 필요가 있다. 본 연구에서는 헌팅을 억제할 목적으로 종래에 사용한 기계식 가바나 대신에 최근에 등장하고 비교적 자유로운 제어규칙을 갖도록 할 수 있는 전자식 가바나를 사용할 때 헌칭이 발생하는 조건이 시뮬레이션을 통하여 조사검토 할 수 있음을 나타내었다. 이 결과에 기초하여 헌칭의 억제는 운전상태에 따라 행할 수 있는 헌팅 억제 규칙을 얻었다.

In this paper, we identified the Black-box system with serious nonlinerity and fast dynamics using Neural Network. This NN have new structure and learned by RLS. It identify system in real-time without priori data. We use this NN to 7-DOF vehicle identification.

Various ropes used at the industrial fields can be used to experiment analyze tension tester development and also as an educational experiment tool. There fore the purpose of this paper is about rope tension tester development satisfying both safety and educational terms.

In this paper, we develope the micro-stepping driver circuit for 5-phase step motor having pentagon type winding and improve the position control performance of the rotor, $0.45^{\circ}$, $0.028125^{\circ}$, $0.0140625^{\circ}$ per step.

항법장치의 핵심요소인 가속도센서와 자이로센서는 선형거리추측(Linear position estimation)과 각 변위 추측(orientation estimation)시 출력 데이터에 포함된 오차성분의 적분에 의하여 시간이 증가함에 따라 선형거리 오차와 각 변위 오차가 누적된다. 이에 따라 본 논문에서는 정밀한 항법을 위한 저가의 IMU (Inertial Measurement Unit)를 설계하고, 오차성분의 사전해석을 통하여 정확한 오차모델을 찾는데 그 목적이 있다.

This paper presents a approach to the adaptive control of nonminimum-phase continuous-time systems. It is shown that pole-zero cancellations can be avoided by using approximate inverse systems. The computer simulation results are presented to illustrate the effectiveness of the proposed method.

A new method of Fault Diagnosis in linear systems using unknown input observer design technique is presented. This method is based upon the fact that the structural uncertainties, actuator faults, and sensor faults of a linear system can be rewritten in unknown inputs. The proposed method can simultaneously estimate the state variables of an actual system, as well as the actuator and sensor faults.

For the last two decades, many researchers have interests in orthogonal functions by reason of its applicability on linear system analysis. But they only used integral operation matrix of orthogonal functions to solve the state space equations. Thus, this paper present some new result of differential operation of block-pulse functions from a numerical point of view.

The orthogonal polynomials have been widely employed to solve control problems, but the LQG(linear quadratic gaussian) problem remains unsolved. In this paper, we obtained the solutions of Riccati equation and covariance matrix Riccati equation by two point boundary problem and matrix fraction method using BPF(Block Pulse Function), respectively. This solutions are solved the problem of the LQG controller design.

In this paper we design the model following ${\mu}$-synthesis control system for optimal fuel-injection of diesel engine using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions that are given by D-K iteration method which can design ${\mu}$-synthesis controller in the state space. These weighting functions are optimized simultaneously in the search domain selected adequately. The effectiveness of this ${\mu}$-synthesis control system for fuel-injection is verified by computer simulation.

A Discrete Event Dynamic System is a system whose states change in response to the occurrence of events from a predefined event set. A major difficulty in developing analytical results for the systems is the lack of appropriate modeling techniques. This paper proposes the use of Real-time Temporal Logic as a modeling tool for the analysis and control of DEDS. The Real-time Temporal Logic Frameworks is extended with a suitable structure of modeling hard real-time constraints. Modeling rules are developed for several specific situations. It is shown how the graphical model can be translated to a system of linear equations and constraints.

The main purpose of this paper is to develop sensing device of joint angle using loss of opfical fiber. The source of light to optical fiber is infrared rays diode, and receiver is a photo transistor. The bent angle of optical fiber is measured with rotary encoder, and The change of voltage due to the loss of light is measured with micro computer PIC16C74. The sensing device may be used to Functional Electrical stimulation(FES) System for Rehabilitation patient.

무인 헬리콥터의 자세 정보를 계측할 수 있는 액체형 균형센서의 특성에 대해 연구하였다. 액체형 균형센서는 시간경과에 따른 누적오차가 없으므로 헬리콥터에 장착하면 장시간동안 균형을 유지시킬 수 있다. 제작된 균형센서의 각 전극에서 측정된 전압으로부터 기울어진 각도를 추정하기 위해 균형센서를 전기적으로 해석하고 측정된 전압과 각도사이의 환산모델을 유도하였다. 구해진 환산모델의 정확성을 실험을 통하여 입증하였다.

The kalman filter which has good estimating capabilities by means of the recursive computation from the previously known of obtained data is usually used for the system estimation in the case of not being directly measurable. The best estimating technique is still open issues on the PWR reactor control system to increase operating contingencies and to predict the safety margins for safer reactor operation. This paper addressed its estimating technique using kalman filter for the more flexible reactor control and showed the reasonable approach for discretization of the continuos-time system for reduction of computation errors.

The systematic and efficient operation of telecommunication power equipments is very important to the safe operation of telecommunication system. To achive that, Korea Telecom has developed a new centralized management system for telecommunication power equipments. The system configuration and main functions for the new developed system are described in this paper.

In this paper, Neuro-Fuzzy Controller(NFC), a fuzzy system realized using a neural network, is to adopt for the multivariable system. In the multivariable system, the interactive effects between the variables should be taken into account. A simple compensator, using the steady-state information can be obtained for open-loop stable systems, is presented to cope with this problem. However, it should be supposed that the plant is unknown to the control system designer, but an estimate of the DC gain has been obtained by carrying out experiments on the plant. Also, if the variables are not combinated completely, it is difficult to design the controller. Therefore, we design a neuro-fuzzy controller which controls a multivariable system with only input output informations, and compare its performance with that of a PI controller. In the proposed controller, the construction of the membership functions and rule base, which is highly heuristic, can be achieved using a training process. This allows the combination of knowledge of human experts and evidence from input-output data.

In this paper, we propose the self-tuning of PID controller using diagonal recurrent neural networks. The characteristic of the proposed structure is on-line adaptive learning scheme in spite of variations of feedback, signals. Control performance is compared with that of neural network based PID controller which was proposed by Iwasa. Computer simulation results show that the proposed controller is effective in controlling of unknown nonlinear plants.

In this paper, a robust speed controller considering the effect of uncertainty (plant parameter variation. external load disturbance. unmodeled and nonlinear dynamics etc..) for induction motor is proposed. Firstly. the dynamic model at nominal case of induction motor is estimated. Based on the estimated model. the IPSC ( Integral - Proportional Speed Controller) is designed. Then a DTRC (Dead-time Robust Controller) combining DTC ( Dead-time Compensator) & SRC (Simple Robust Controller) is designed to reduce the effects of parameter variation and external disturbance. Some simulated results are provided to demonstrate the effectiveness of the proposed controller.

The spectrum-recovery scheme in Hadamard transform spectroscopy is commonly implemented with a fast Hadamard transform (FHT). When the Hadamard or simplex matrix corresponding to the mask does not have the same ordering as the Hadamard matrix corresponding to the FHT, a modification is required. When the two Hadamard matrices are in the same equivalence class, this modification can be implemented as a permutation scheme. This paper investigates permutation schemes for this application. This paper is to relieve the confusion about the applicability of existing techniques, reveals a new, more efficient method: and leads to an extension that allows a permutation scheme to be applied to any Hadamard or simplex matrix in the appropriate equivalence class.

This paper is concerned with the design of a suboptimal Kalman filter with robust state estimation performance for system models represented in the state space, which are subjected to parameter uncertainties in both the state and measurement matrices. Under the assumption that the uncertain system is quadratically stable, if the augmented system composed of the uncertain system and the filter is controllable, the proposed filter can provide the upper bound of the estimation error variance for all admissible uncertain parameters. This upper bound can be represented as the convex function of a parameter introduced in the design procedure, and the optimized upper bound of the estimation error variance can also be found via the optimization of this convex function.

Canonical Chua's circuit is a simple electronic circuit which exhibits a variety of bifurcation phenomena and attractors. It consists of two capacitors, an inductor, two linear resistors, and a nonlinear resistor. When the circuit exhibits chaotic signals, the nonlinear resistor of canonical Chua's circuit may have three different voltage - current characteristics. In this paper, the design methodology for practical implementation of the nonlinear resistors which have all these characteristics is described. In addition, the effectiveness of result is shown by not only the MATLAB simulation but also the PSPICE simulation.

In this paper, fuzzy logic system equipped with the back-propagation training algorithm as identifiers for nonlinear dynamic systems is described. To improve its performance, Jacob's delta-bar -delta rule is adapted in adjusting stepsize ${\alpha}$, and only y and ${\alpha}$ updating algorithm is suggested. In identifying and predicting the chaotic time series, suggested method is better than Li-Xin Wang's method,[1]

A fuzzy controller is based on o fuzzy logic that is so effective to represent uncertain phenomena of real world end mote its approximation. In this paper, A fuzzy controller which equipped with adaptive control algorithm is described. Proposed fuzzy controller applied to a boll on boon system shows a good performance.

In this paper, a transmitter and a receiver using two identical Chua's circuits are proposed and a wire synchronizations are investigated. As several problems have been found in both the drive-response synchronization and the coupled synchronization in the previous researches, a new drive-coupled synchronization theory is proposed that can be applicable to wire communication. Since the synchronization of the wire transmission system is impossible by coupled synchronization, theory having both the drive-response and the coupled synchronization is proposed. As a result, the chaos synchronization has delay characteristics in the wire transmission system caused by the line parameters L and C.

This paper deals with the problem of finding robust controller based upon a pole assignment method for a plant with parameter perturbations. This case is not a problem of Interval polynomial family but a problem of poly topic polynomial family. As a method of stability test, we used GKT(Generalized Kharitonov Theorem) having computational advantage.

전력계통의 주파수는 전력의 수요와 공급량의 평형상태에 따라 수시로 변동하며, 각 발전소에서는 이 주파수를 입력 신호로 사용하여 발전기의 출력을 제어하고 있다. 본 논문에서는 국내에서 운영하고 있는 한 개스터빈 발전소의 터빈제어 시스템을 모델로 하여 주파수 추종성에 영향을 미치는 파라미터들을 분석하고, 시뮬레이션을 통해 주파수 추종성을 향상시키기 위한 방안을 제시하였으며, 현장에 적용한 결과를 통해 제안된 주파수 추종성 향상방안의 타당성을 검증하였다.

프로세스에서의 시간지연은 프로세스의 제어에 있어서 어려움을 초래하며, 시스템의 성능저하의 원인이 되고 있다. 이러한 프로세스의 시간지연을 극복하고자 해서 제안된 제어기의 구조가 기존의 제어기에 smith predictor를 결합한 형태이다. 본 논문에서는 몇 개의 프로세스를 선택하고, PI 제어기와 smith predictor와 결합되어진 PI 제어기에 대해서 프로세스의 지연시간에 따른 컴퓨터 모의실험을 통해 smith predictor의 효용성을 논하고자 한다.

북제주 내연기관 발전기는 설비 노후로 인하여 경미한 고장이 점차 확대되고 기관 핵심 부품들의 손상이 증가하여 발전원가를 상승시키는 주요요인이 되고 있었다. 즉 정비 부품 교체 비용이 증가하고, 복구 시간이 장시간 소요되는 등 문제점을 안고 있었다. 이러한 문제점을 해결하기 위하여, 기관의 핵심요소인 실린더와 베어링의 상태를 연속 감시하고, 고장을 미리 발견 조치할 수 있는 컴퓨터시스템에 대하여 논하고자 한다.

현재 우리나라 발전소에는 ABB(Asea Brown Bovery), Bailey, Westinghouse와 같은 여러 외국 제작사의 분산제어시스템(DCS)이 도입되어 운전되고 있다. 발전소의 만족할 만한 운전성능을 얻기 위해 구성된 제어루프에 가장 널리 이용되고 있는 PID제어기의 기본개념은 이상형 PID제어기와 동일하지만 제작사별로 구현하는 방법에 있어서 다소의 차이가 있다. 본 논문에서는 먼저 제작사에서 제공한 PID 제어블럭의 알고리즘을 비교한다. 이들 중에서 가장 많이 이용되는 직렬형 PID 제어기를 Ziegler-Nickels 주파수 응답법에 의해 산출된 파라미터보다 직렬형으로 변환된 파라미터를 사용하면 응답특성이 개선되고, 미분동작에서 미분필터 요소를 추가할 경우 프로세스의 안정도를 개선할 수 있다는 것을 컴퓨터 모의실험을 통하여 검증한다.

전력사업에 있어 그 기본이 되는 발전소는 현재 복잡화되어 가고 있는 산업사회의 전력수요에 대한 대폭적인 증가 추세에 따라 발전소에서는 보다 효율적이며 합리적이고 경제적인 전력공급을 위해 전력생산에 대한 신뢰성 향상 및 안정성 확보는 물론, 효율성이 높은 운전이 요구되고 있다. 본 논문에서는 상호간섭이 많은 다변수 비선형 시스템인 발전소를 제어하기 위해 적용된 선진국들의 분산제어시스템(DCS, Distributed Control System)의 구조를 분석하고 향후 발전소용 DCS의 기술동향 및 선택을 위해 고려될 사항들을 알아보고자 한다.

본 논문에서는 직접신경회로망제어기(DNNC)를 사용하여 결합된 PI제어기의 이득을 구하여 보일러 터빈시스템을 제어하고자 한다. 직접신경회로망제어기는 플랜트의 동특성을 학습시키는 에뮬레이터 없이 제어입력에 대한 플랜트의 동작방향에 대한 정보만을 사용하여 신경회로망을 학습시키고, 이 신경회로망을 사용하여 제어대상 플랜트인 다중입출력플랜트를 제어하기 위하여 결합된 PI 제어기의 이득을 구한다. 컴퓨터 시뮬레이션을 통하여 제안한 알고리즘의 타당성을 입증하고자 한다.

발전설비를 안정적이고도 효율적으로 운용하기 위해서는 완벽한 감시기능을 갖추는 것이 필수적이다. 발전소에 설치된 Bailey사 제품의 Infi-90 시스템은 발전소 제어 및 데이터로깅까지 컴퓨터를 사용하지 않고도 할 수 있는 폭넓은 응용 범위를 가지며, 몇 개의 루프로 구성된 소규모 계장에서부터 대규모 계장에까지 적용할 수 있는 확장성이 큰 시스템이다. 본 논문에서는 Infi-90 시스템에서 제공하는 접속장치를 활용하여, PC를 이용한 데이터 모니터링시스템 개발에 관하여 논하고자 한다.

A new improved excitation control system for power plant synchronous generators has been developed by KEPRI (Korea Electric Power Research Institute). The reliability of the excitation system is increased by designing a dual channel automatic voltage regulator(AVR). Also the performance of the excitation system is improved by Self-Tuning adaptive Controller. A software package is developed for the excitation control system, and a field test is conducted to verify the system performance.

This paper presents the development of Distributied Control System for Bookjeju fossil plant. The original analog control system for the power plants has a complex and large-scale structure in their hardware configuration and much difficulties have been experienced for maintenance due to lack of original components. This system connects three different control systems in Bookjeju fossil plant by cue network, The result shows that optimal Distributied Control System has standardization of control system, effective operation management and convenient maintenance of power plant.

본 논문에서는 적응제어계통의 강인성을 향상시키기 위한 새로운 알고리즘을 제시한다. 이 적응 알고리즘은 외란의 영향을 상쇄시키고 Lyapunov 도함수 $V{\le}0$가 되도록 한다. 그 결과로서 외란이 존재하는 경우만 아니라 이상적인 경우에도 출력오차가 0에 수렴한다. 또한 컴퓨터 시뮬레이션과 DC 서보 전동기의 위치제어 실험을 통하여 $e_1$ 변형법과 실험결과를 비교함으로써 제안한 알고리즘의 타당성을 보여준다.

In this paper, we study the idle speed control of the spark ignition engine. Engine idle speed control is a difficult problem because of troublesome characteristics such as severe process nonlinearities, variable time delays, time-varying dynamics and unobservable internal system states and disturbances. We investigate the intelligent control algorithms such as neural network controller and fuzzy controller for 4-cylinder 4-stroke engine.

In this paper, we present a fast and robust algorithm for the design of fuzzy controller and identifying fuzzy model from numerical data by combining the cluster estimation method with a linear least squares estimation procedure. The proposed method is compared with Adaptive Neuro-Fuzzy Inference System(ANFIS) as the standard example of neuro-fuzzy model. Finally we will show its usefulness and effectiveness for the design of fuzzy controller of a cart-pole system and fuzzy modeling for the coagulant dosing of a water purification system.

A $H_{\infty}$ adaptive controller is designed by using polynomial approach. The $H_{\infty}$ robust controllers for adaptive system were designed by Grimble. But they did not minimize the mixed sensitivity ra cost function which is the re sum of weighted sensitivity and complementary sensitivity terms Moreover pole placement is dependent of cost function. In this paper, the mixed sensitivity re cost function is minimized by employing the Youla parameterization and polynomial approach at the same time. And pole plaement is independent of weighting function.

In the design of nonlinear control systems separation principle does not hold. Moreover even an exponentially decaying disturbances can destabilize a nonlinear system and lead to finite escape time from certain initial conditions. So we present a simple output feedback speed controller of induction motors which is designed to minimize the effects of observation error using the Kanellakopoulos et al's interlaced controller-observer design method. Simulation shows that the proposed controller has desired performance like another complex controllers.

In this paper, we introduce a new adaptive controller for induction motor based on singular perturbation theory. The design of 5th induction motor was changed for the 3rd modeling using the singular perturbation method. The resulting boundary layer and quasi-steady-state systems are made exponentially stable. Therefore the statements of Tychonov's theorm are valid for an infinite time interval for induction motor, too.

This paper is attempt to develop an active controller for the vibration of tall civil structures due to earthquake-induced ground acceleration. Various active control methods are applied to an 8 story base isolated system(BIS) with a fumed mass damper(TMD) at the base of the building. The results are also investigated.

This paper deals with the tracking control problem of robotic manipulators with unknown or changing dynamics. The torque input applied to the joint actuators is determined at every instance by the identification model that best approximates the robot dynamics. The best of the identified model is chosen by the proposed switching mechanism with fuzzy inference of the manipulator in an indirect adaptive controller architecture. Simulation results are also included to demonstrate the improvement in the tracking performance when the proposed method is used.

The marine diesel engine have been widely applied with a mechanical hydraulic governor to control the ship speed for long time. But it was recently very difficult for the mechanical hydraulic governor to control the speed of engine under the condition of low speed and low load because of jiggling by rough fluctuation of rotating torque and hunting by dead time of diesel engine. In order to analyze the speed control system the transfer function was converted from z to w transformation. The author proposed velocity control system with feedback loop by PID controller in order to stabilize for unstable area. The influence of dead time was discussed by Nichols chart and unit step response curve. It was confirmed through computer simulation that the performance improvement of a mechanical hydraulic governor can be obtained by PID controller.

The simulated annealing(SA) algorithm is a stochastic strategy for search of the ground state and a powerful tool for optimization, based on the annealing process used for the crystallization in physical systems. It's main disadvantage is the long convergence time. Therefore, this paper proposes a stochastic algorithm combined with conventional deterministic optimization method to reduce the computation time, which is called SDS(Stochastic-Deterministic-Stochastic) method.

In this paper, we applied self-tuning controller with I-PD type to process with time delay's. Process parameters are estimated by the recursive least squares algorithm, and optimal gains are obtained. This paper shows self-tuning controller with I-PD type performs better than that of general PID type for the nonlinear system with sudden change of set-points.

An optimal tuning algorithm of scaling factors is presented in this paper to automatically improve the performance of fuzzy controller. Especially, fuzzy controller has determined an moderate Scaling factor through trial and error. The presented method estimates automatically the optimal values of I/O scaling factors, using modified steepest descent method and this optimal tuning is for nonlinear input/output scaling factors. Simulation results verify the validity of the presented method.

In this paper, an adaptive control scheme is proposed for slowly time-varying discrete-time nonlinear dynamic system. CMAC networks are employed to identify system from input-output data and to construct the controller based on this identifer. All of learning procedures are performed on-line. Computer simulation result shows the usefulness of the proposed scheme.

The mechanical properties of a hot rolled steel is mostly governed by a cooling control on the run out table. During the cooling control, the hot rotted steel performs a metallurgical transformation(austenite ${\to}$ ferrite) which can be measured with a magnetic flux detector. The magnetic flux detector consisting of exciting and detecting coil can estimates the metallurgical transformation by measuring the variation of permeability in steel. We developed the method of detecting the magnetic property of hot rolled steel and processing the measured signal, Which makes possible to measure on-line metallurgical transformation.

In order to prevent the belt from being damaged by metal pieces, we developed multicoil-type metal detection system. This detects the presence of belt clips and position of metal pieces in ores being transported on conveyor belt. In this research, our coil sensor of multicoil-type metal detection system is divided into two parts, exciting part (transmitter coil) and sensing part composed of two receiver coils. Each receiver coil has several coils in the direction of belt width. Multicoil-type metal detection system is operated by supplying a transmitter coil with electric power resources to generate magnetic field, and then the change of magnetic flux resulted from a metal piece on the conveyor be a is induced into sensing coils. We can prevent detector from failing to catch metal pieces due to high threshold level produced by steel belt clips and male the sensitivity of belt-width direction uniform by using multicoil-type metal detection system. Besides, this developed system can recognize precise position and size of metal piece. The experiments shows that our multicoil-type metal detection system has better performances than the conventional metal piece detector.

This paper discusses approximate modelling of discrete-time linear time-varying system(LTVS). The wavelet transform is considered as a tool for representing and approximating a LTVS. The joint time-frequency properties of wave analysis are appropriate for describing the LTVS. Simulatly results is included to illustrate the popential application of the technique.

The characteristics of ball and beam system using fuzzy inference technique can be described by fuzzy modeling. Therefore, this paper introduces a technique for fuzzy structure identification of nonlinear Input-output relation- ship using an adaptive fuzzy inference system. And the simulation result using adaptive fuzzy inference technique shows its effectiveness for fuzzy structure identification of nonlinear system.

This paper describes a control method of tank level using Fuzzy Inference Technique. In General, to control tank level without a dangerous overflow and with a high accuracy is difficult because of high order time delay and nonlinearity. None the less, the hardware controller using 80586 Microprocessor with DT-2801 board in this paper was successfully implemented, through a series of simulations and experiments, the superiority of the proposed fuzzy controller ta a conventional PID one was investigated.

This paper proposes the systematic auto-tuning method for fuzzy controller using genetic algorithm(GA). In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge and relies to a great extent on heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored. Proposed genetic algorithm searches the optimal rule structure, parameters of membership functions and scaling factors simultaneously and automatically by a new genetic coding format. Inverted pendrum system is provided to show the advantages of the proposed method.

This paper describes the design and implementation of a fuzzy temperature control system to control the water temperature in plant. For evaluating the performance of a fuzzy controller, the experiment results of a fuzzy controller are compared with these of a conventional PID controller which provides an auto-tuning function. The experiment results show that the proposed controller has a good control performance and is robust to external disturbance.

The traffic congestion caused by the exploding increase of vehicles became one of the severest social problems. Among the various approaches to solve this problem, controlling the length of traffic signals appropriately according to the individual traffic situation would be the most plausible and cost-effective method. To design a traffic signal controller which has such a property as adaptive decision-making process, we adopt fuzzy logic control method(fuzzy traffic signal controller), Moreover, using genetic algorithms we obtain an optimized fuzzy traffic signal controller (GA-fuzzy traffic signal controller). To evaluate and validate the proposed fuzzy and GA-fuzzy traffic signal controller, simulation results are presented.

This paper proposes the structure and parameter optimization technique of fuzzy neural networks using genetic algorithm. Fuzzy neural network has advantages of both the fuzzy inference system and neural network. The determination of the optimal parameters and structure of the fuzzy neural networks, however, requires special efforts. To solve these problems, we propose a new learning method for optimization of fuzzy neural networks using genetic algorithm. It can optimize the structure and parameters of the entire fuzzy neural network globally. Numerical example is provided to show the advantages of the proposed method.

When a fault is generated somewhere in ANC system, it makes undesirable effects on the system's stability and performance. So, reliability of the system should be considered before we set up the system in a field. In this paper, to improve the reliability of the ANC system, we proposed a fault detection algorithm. To show the detectability of fault, computer simulation was performed. As a result, the algorithm could detect 3 types of fault and where they happened and make the system stay stable.

The parity relation approach for the fault detection and isolation (FDI) of a large diesel engine actuator position servo system is presented. Main purpose of the FDI system is to detect and isolate two important faults, actuator fault and sensor fault, that, if not detected and compensated, degrade the overall system performance. Simulation results are given to show the practical applicability of the FDI scheme.