APPLICATION AND ROBUSTNESS DESIGN OF FUZZY CONTROLLER FOR RESONANT AND CHAOTIC SYSTEMS WITH EXTERNAL DISTURBANCE-Reference-Cited by-同舟云学术

APPLICATION AND ROBUSTNESS DESIGN OF FUZZY CONTROLLER FOR RESONANT AND CHAOTIC SYSTEMS WITH EXTERNAL DISTURBANCE

Published:2005-06 Issue:03 Volume:13 Page:281-295
ISSN:0218-4885
Container-title:International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
language:en
Short-container-title:Int. J. Unc. Fuzz. Knowl. Based Syst.

Author:

HSIAO FENG-HSIAG¹,CHIANG WEI-LING²,CHEN CHENG-WU²,XU SHENG-DONG³,WU SHIH-LIN⁴

Affiliation:

1. Department of Electronic Engineering, National United University, No. 1, Lien Da, Miaoli 360, Taiwan, R.O.C.

2. Department of Civil Engineering, National Central University, No. 300, Jhongda Road, Wu Chuan Li, Jhongli, Taoyuan County 32001, Taiwan, R.O.C.

3. Department of Electrical and Control Engineering, National Chiao Tung University, No. 1001, Ta Hsueh Road, Hsinchui 30039, Taiwan, R.O.C.

4. Department of Computer Science and Information Engineering, Chang Gung University, No. 259, Wen Hwa 1st Road, Kweishan, Taoyuan County 333, Taiwan, R.O.C.

Abstract

A robustness design of fuzzy control via model-based approach is proposed in this paper to overcome the effect of approximation error between nonlinear system and Takagi-Sugeno (T-S) fuzzy model. T-S fuzz model is used to model the resonant and chaotic systems and the parallel distributed compensation (PDC) is employed to determine structures of fuzzy controllers. Linear matrix inequality (LMI) based design problems are utilized to find common definite matrices P and feedback gains K satisfying stability conditions derived in terms of Lyapunov direct method. Finally, the effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic and resonant systems.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218488505003461

Reference16 articles.

1. Simplifying fuzzy rule-based models using orthogonal transformation methods

2. An approach to fuzzy control of nonlinear systems: stability and design issues

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