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Title: Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm
Authors: Lam, HK
Ling, SH
Leung, FHF 
Tam, PKS
Issue Date: 2001
Source: The 10th IEEE International Conference on Fuzzy Systems : meeting the grand challenge : machines that serve people : The University of Melbourne, Australia, December, 2001, Sunday 2nd to Wednesday 5th, p. 908-911
Abstract: This paper tackles the control problem of nonlinear systems subject to parameter uncertainties based on a fuzzy logic approach and the genetic algorithm (GA). In order to achieve a stable controller, TSK fuzzy plant model is employed to describe the dynamics of the uncertain nonlinear plant. A fuzzy controller and the corresponding stability conditions will be derived. The parameters of the fuzzy controller and the solution to the stability conditions are determined using GA. In order to obtain the optimal performance, the membership functions of the fuzzy controller are obtained automatically by minimizing a defined fitness function using GA.
Keywords: Control system synthesis
Fuzzy sets
Genetic algorithms
Mathematical models
Matrix algebra
Membership functions
Nonlinear control systems
Optimal control systems
Parameter estimation
System stability
Uncertain systems
Publisher: IEEE
ISBN: 0-7803-7293-X
Rights: © 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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