• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.158-164
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• 1996

In this paper, we consider the problem of robust stability of discretd time-delay systems subjected to perturbations. Two classes of perturbations are treated. The first one is the nonlinear norm-bounded perturbation, and the second is the structured time-varying parametric perturbation. Based on the discrete-time Lyapunov stability theory, several new sufficient conditions for robust stability of the system are presented. From these conditions, we can estimate the maximum allowable bounds of the perturbations which guarantee the stability. Finally, numerical examples are given to demonstrate the effectiveness of the results.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1473-1476
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• 1997

This paper presents a scheme for continuous-time fuzzy modelling of nonlinear systems, based on the adjustment technique and the genetic algorithm technque. The fuzzy model is characterized by fuzzy "If-then" rules whcih represent locally linear input-output relations whose consequence part is defined as subsystem of a nonlinear system. To compute the final output and deal with the initialization and unmeasurable signal problems in on-line estimatio of the fuzzy model, a discrete-time model is obtaned. Then the parameters of both the premis and consequence of the fuzzy model are adjusted on-line by a genetic algorithm. A simulation work is carried out to demonstrate the effectiveness of the proposed method.ed method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.30-39
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• 2000

In order to linearize the nonlinear systems, two different methods(i.e. state coordinate change and feedback) are usually used. In this paper, we consider the multi-input discrete-time nonlinear systems and obtain the necessary and sufficient conditions for both the linearization problem by state-coordinate change and the feedback linearization problem. The way of finding state coordinate change and state feedback which linearize the given system is also given in the proof.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.397-406
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• 1997

In this paper we introduce GESS method and show that dynamics of the system ｙ＇=A(s,t,y) ｙ is more faithfully approxi-mated by GESS method that by Euler method. Numerical experiments are given for the comparison of GESS method with Euler method.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.653-658
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• 2001

In this paper, we find the necessary and sufficient conditions for the discrete time nonlinear system to be transformed into observable canonical form by state coordinates change. Unlike the continuous time case, our theorems give the desired state coordinates change without solving partial differential equations. Also, our approach is applicable to both autonomous systems and control systems by slight change of the definition of the vector field.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.912-914
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• 1999

In this paper, the feedback linearization technique is used with the sliding mode control for discrete nonlinear systems. This combination of the two control techniques is achieved by Proposing a novel sliding surface which has the nominal dynamics of the original system controlled by feedback linearization technique. Its design is based on the augmented system whose dynamics have a higher order than that of the original system. The reaching Phase is removed by using an initial virtual state which makes the initial sliding function equal to zero.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.125-128
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• 1987

We investigate the feedback linearizability of nonlinear discrete-time system s of a specific form, $x_k=G_{u_k}oF(x_k)$ where F is a diffeomorphism and [$G_{u_k}$] forms an one parameter group of diffeomorphisms. This structure represents a class of systems which are state equivalent to linear ones and approximates the sampled data model of a continuous-time system. It is also considered a relationship between linearizability and discretization.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.606-613
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• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1133-1138
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• 1991

A control of nonlinear system is motivated by the fact that all real plants are nonlinear systems and model identification introduces parameter errors. The purpose of this study is to design a Discrete Variable Structure Controller(DVSC) for single-rod hydraulic cylinder system. The model contains uncertain parameters which we known to lie upper and lower bounds. In the design of DVSC, the boundary layer concept was adopted to reduce cattering. The DVSC was evaluated through digital computer simulation and compared with a VSC (analog controller).

• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.1975-1987
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• 2005

An input time delay always exists in practical systems. Analysis of the delay phenomenon in a continuous-time domain is sophisticated. It is appropriate to obtain its corresponding discrete-time model for implementation via digital computers. In this paper a new scheme for the discretization of nonlinear systems using Taylor series expansion and the zero-order hold assumption is proposed. The mathematical structure of the new discretization method is analyzed. On the basis of this structure the sampled-data representation of nonlinear systems with time-delayed multi-input is presented. The delayed multi-input general equation has been derived. In particular, the effect of the time-discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. Additionally, hybrid discretization schemes that result from a combination of the scaling and squaring technique (SST) with the Taylor series expansion are also proposed, especially under conditions of very low sampling rates. Practical issues associated with the selection of the method's parameters to meet CPU time and accuracy requirements, are examined as well. A performance of the proposed method is evaluated using a nonlinear system with time delay maneuvering an automobile.