Adaptive fuzzy controller for nonlinear systems via genetic algorithm

Authors:
P. C. Chen;W. L. Chiang;C. W. Chen;C. H. Tsai
Affiliations:
Department of Civil Engineering, National Central University, Chung-li, Taiwan, R.O.C.;Department of Civil Engineering, National Central University, Chung-li, Taiwan, R.O.C.;Department of Logistics Management, Shu-Te University, Kaohsiung, Taiwan, R.O.C.;The Center of Tour Geographical Information Systems, Taiwan Hospitality & Tourism College, Shoufong Township, Hualien County, Taiwan, R.O.C.
Venue:
AEE'08 Proceedings of the 7th WSEAS International Conference on Application of Electrical Engineering
Year:
2008

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Abstract

In this paper, we describe a method of stability analysis for a GA-Based reference adaptive fuzzy sliding model controller for the handling of these problems for a nonlinear system. Firstly, an uncertain and nonlinear plant for the tracking of a reference trajectory is well approximated and described via a fuzzy model involving fuzzy logic control rules. Then, the initial values of the consequent parameter vector are decided via a genetic algorithm. Finally, an adaptive fuzzy sliding model controller is derived to simultaneously stabilize and control the system. The stability of the nonlinear system is ensured by the derivation of the stability criterion based upon Lyapunov's direct method.