• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.712-717
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• 2007

This paper is concerned with the problem of state feedback control of continuous-time nonlinear Markovian jump systems, which are represented by Takagi-Sugeno fuzzy models. A new method for designing state feedback stabilizing controllers is presented in terms of solvability of a set of linear matrix inequalities (LMIs), and it is shown that the new design method provides better or at least the same results of the existing method in the literature. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.81-87
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• 1993

In this paper robust stability conditions are obtained for linear dynamical systems under structured nonlinear time-varying perturbations, using absolute stability theory and the concept of dissipative systems. The conditions are expressed in terms of solutions to linear matrix inequality(LMI). Based on this result, a synthesis methodology is developed for robust feedback controllers with worst-case H$_{2}$ perforrmance via convex optimization and LMI formulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.453-456
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• 1996

In this paper, the direct adaptive control using neural networks is presented for the control of chaotic nonlinear systems. The direct adaptive control method has an advantage that the additional system identification procedure is not necessary. In order to evaluate the performance of our controller design method, two direct adaptive control methods are applied to a Duffing's equation and a Lorenz equation which are continuous-time chaotic systems. Our simulation results show the effectiveness of the controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.972-975
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• 1996

This paper presents a sufficient condition for robust stability of discrete-time systems with delayed nonlinear perturbations. Using state evolution method, the bound on the norms of nonlinear perturbation which guarantees the exponential stability of the systems, is found. The numerical example is given to illustrate the results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.95.4-95
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• 2001

In this paper, we proposed and analyze an robust adaptive control scheme for uncertain nonlinear systems using Universal function approximators. The proposed scheme completely overcomes the singularity problem which occurs in the indirect adaptive feedback linearizing control. No projection in the estimated parameters and no switching in the control input are needed. The stability of the closed-loop systems is guaranteed in the Lyapunov standpoint.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.83.5-83
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• 2002

Perspective dynamical systems arise in machine vision, in which only perspective observation is available, and the essential problem is to estimate the state and /or unknown parameters for a moving rigid body based on the observed information. This paper proposes and studies a Luenberger-type observer for perspective tim e-varying linear systems. In particular, assuming a given perspective time-varying linear system to be Lyapunov stable and to satisfy some sort of observability condition, it is shown that the estimation error converges exponentially to zero. Finally, a simple numerical exam pie is presented to illustrate the result obtained.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 춘계학술대회 학술발표 논문집
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• pp.73-76
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• 1997

This paper proposes the fuzzy logic-based fast gain scheduling(FFGS) controller for regulation problem in nonlinear systems. It utilizes which reflects the derivative information on the original scheduling variable in order to achieve better performance than the existents. Moreover, we apply the proposed control scheme to control active suspension systems with nonlinear components.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.122-125
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• 2000

The paper describes the adaptation of evolutionary fuzzy model ins (EFM) in developing global function approximation tools for use in genetic algorithm based optimization of nonlinear structural systems. EFM is an optimization process to determine the fuzzy membership parameters for constructing global approximation model in a case where the training data are not sufficiently provided or uncertain information is included in design process. The paper presents the performance of EFM in terms of numbers of fuzzy rules and training data, and then explores the EFM based sizing of automotive component for passenger protection.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.443-443
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• 2000

A systematic scheme is developed fer the design of new adaptive feedback linearizing controllers for nonlinear systems. The developed adaptation law estimates the uncertain time-varying parameters using the structure of diffeomorphisrn. Our scheme is applicable to a class of nonlinear systems which violates the restrictive parametric-pure-feedback condition [4]-[6].

• 전기학회논문지
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• 제63권4호
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• pp.502-508
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• 2014

In this paper, a delay-dependent $H_{\infty}$ filtering problem is investigated for discrete-time delayed nonlinear systems which include a more general sector nonlinear function instead of employing the commonly used Lipschitz-type function. By using the Lyapunov-Krasovskii functional approach, a less conservative sufficient condition is established for the existence of the desired filter, and then, the corresponding solvability condition guarantee the stability of the filter with a prescribed $H_{\infty}$ performance level. Finally, two simulation examples are given to show the effectiveness of the proposed filtering scheme.