• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.140-143
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• 2001

In this paper, a control problem of the Takagi-Sugeno(TS) fuzzy system with time-varying input delay is considered. It is well known that the delay is one of the major sources responsible for the instability of the controlled system. A systematic design technique is developed based on the Lyapunov-Razumikhin stability theorem. A sufficient condition for the global asymptotic stability of the TS fuzzy systems is formulated in terms of linear matrix inequalities (LMIs). The derived condition can deal with any time-varying input delay within the admissible bound. The effectiveness of the proposed controller design technique is demonstrated by a numerical simulation.

• Journal of Institute of Control, Robotics and Systems
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• 제12권3호
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• pp.227-232
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• 2006

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear system which may also contain system uncertainties. The continuous-time uncertain TS fuzzy model is first contructed to represent the uncertain nonlinear system. A parallel distributed compensation(PDC) technique is then used to design a fuzzy-model-based controller for both stabilization. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using a globally intelligent digital redesign method. This new technique is designed by a global matching of state variables between analog control system and digital control system. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear systems with uncertainties. Finally, Chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• Proceedings of the KIEE Conference
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1856-1857
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• 2011

Induction motor is nonlinear multivariable system. It is not easy to control precisely. Usually Induction motor need linearized model in order to make it easy to control. In this paper, linearized model of nonlinear model in induction motor can change by using TS Fuzzy Identification.

• Journal of the Korean Institute of Intelligent Systems
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• 제15권7호
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.35.2-35
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• 2002

$\textbullet$ Introduction $\textbullet$ An affine fuzzy system $\textbullet$ The stabilization of an affine fuzzy system $\textbullet$ Iterative LMI algorithm for the stabilization $\textbullet$ A numerical example $\textbullet$ Conclusion

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.142-145
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• 2000

A new robust load-frequency control (LFC) methodology is proposed for nonlinear power systems with the valve position limits of the governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TS fuzzy model with parametric uncertainties. The intelligent digital redesign technique for the uncertain nonlinear power system is also studied. The effectiveness of the proposed robust fuzzy LFC controller design method is demonstrated through a numerical simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.139-145
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• 2002

In this paper, we proposed an intelligent digital redesign method for a class of fuzzy-model-based controllers, effective fur stabilization of continuous-time nonlinear systems. The TS fuzzy model is used to expend the results of the digital redesign technique to nonlinear systems. The proposed method utilized the recently developed LMI technique to obtain a digitally redesigned fuzzy-model-based controller. The intelligent digital redesign problem is converted to equivalent problem, and the LMI method is used to find the digitally redesigned fuzzy-model-based controller. The stabilization conditions of TS fuzzy model are derived for stabilization in the sense of Laypunov stability. In order to demonstrates the effectiveness and feasibility of the proposed controller design methodology, we applied this method to the single link flexible-joint robot arm.

• Journal of Institute of Control, Robotics and Systems
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• 제7권7호
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• pp.589-596
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• 2001

In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

• Journal of the Korean Institute of Intelligent Systems
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• 제18권6호
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• pp.762-767
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• 2008

This paper introduces a $L_{\infty}$-gain state feedback fuzzy controller design for the time delay nonlinear system represented by Takagi-Sugeno(T-S) fuzzy model. First, the T-S fuzzy model is employed to represent the time delay nonlinear system. Next based on the fuzzy model, a fuzzy state feedback controller is developed to achieve $L_{\infty}$-gain performance. Finally, sufficient conditions are derived for $L_{\infty}$-gain performance. The sufficient conditions are formulated in the format of linear matrix inequalities (LMIs). The effectiveness of the proposed controller design methonology is finally demonstrated through numerical simulations.