• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.5-8
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• 2003

This paper we study the exact controllability for the nonlinear fuzzy control system in E$_{N}$$^{n}$ by using the concept of fuzzy number of dimension n whose values are normal, convex, upper semicontinuous and compactly supported surface in R$^{n}$ . fuzzy number of dimension n ; fuzzy control ; nonlinear fuzzy control system ; exact controllabilityty

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1165-1168
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• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Network(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Radial Basis Function Networks(RBFN). The learning with RBFN is fast and precise. This paper discusses RBFN as identification procedure is based on a nonlinear dynamical systems. and A design method of model follow control system based on RBFN controller is developed. As a result of applying this method to inverted pendulum, the simulation has shown that RBFN can be used as identification and control of nonlinear dynamical systems effectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.33.2-33
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• 2001

The robust stability condition for sampled-data control systems with a sector nonlinearity was presented in our previous paper. Although it is applicable only to the sampled-data control system of a certain class, a usual discretetime control system can belongs to this type of class. This paper analyzes the amplitude dependent behavior of nonlinear sampled-data (i.e., discrete-time) control systems in a frequency domain. By considering restricted areas (sectors) in the nonlinear characterisitic, the existence of a sustained oscillation is estimated, and the relationship between the stable/unstable conditions and the result derived from describing function is compared. Based on these considerations, the stabilization of nonlinear discrete-time control systems is examined in the frequency domain.

• 제어로봇시스템학회논문지
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• 제17권6호
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• pp.573-578
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• 2011

We propose a switching-based adaptive state feedback controller for a class of nonlinear systems that have uncertain nonlinearity. The base of the proposed conditions on the nonlinearity is the feedforward form, then it is extended via a nonlinear function containing all the states and the control input. As a result, more generalized systems containing feedforward and nonfeedforward terms are allowed as long as the ratio condition of the nonlinear function is satisfied. Moreover, the information on the growth rate of nonlinearity is not required a priori in our control scheme.

• 제어로봇시스템학회논문지
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• 제20권3호
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.407-412
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• 2004

This paper presents a new algorithm for the closed-loop $H_{\infty}$ composite control of singularly perturbed nonlinear systems with a exogenous disturbance, using the successive Galerkin approximation(SGA). The singularly perturbed nonlinear system is decomposed into two subsystems of a slow-time scale and a fast-time scale via singular perturbation theory, and two $H_{\infty}$ control laws are obtained to each subsystem by using the SGA method. The composite control law that consists of two $H_{\infty}$ control laws of each subsystem is designed. One of the purposes of this paper is to design the closed-loop $H_{\infty}$ composite control law for the singularly perturbed nonlinear systems via the SGA method. The other is to reduce the computational complexity when the SGA method is applied to the high order systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.208-208
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• 2000

In realistic control systems, the nonlinear salutation attributes of the control actuator due to physical limitations should be taken into account. This nonlinear saturation of actuators may cause not only deterioration of the control performance but also a large overshoot during start-up and shut-down. As the overshoot increases, the system may become oscillatory unstable. In this paper, the supervisor implementation which guarantees good performance lot saturation operation and prevents reset wind-up is presented. Moreover, the sufficient conditions of the stability for saturated systems using supervisory control with a dynamic controller are provided in the discrete-time domain. A numerical example is illustrated to depict the efficiency of supervisory control for a typical saturated production-distribution system controlled by a discrete-time dynamic controller and to validate basic results by simulation.

• 대한전기학회논문지
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• 제45권3호
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• pp.393-398
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• 1996

In this paper, we consider H.inf. control of nonlinear systems which have not only additive uncertainties but also input-multiplicative uncertainties. Using the relation between the L$_{2}$ gain of a nonlinear system and the Hamilton-Jacobi-Isaacs inequality, we define

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1213-1218
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• 1993

Variable structure control is applied to the robust output tracking control problem of general nonlinear multi-input multi-output (MIMO) systems. Using the concept of relative degree and minimum phase, input/output(I/O) linearization is undertaken. For I/O the linearized system, a new sliding hyperplanes design method is proposed. In this procedure, we can construct very robust and efficient sliding mode controller for general nonlinear systems of relative degree higher than two. The control results are illustrated by adopting a numerical example.