Published in

10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)

DOI: 10.1109/fuzz.2001.1009103

Links

Tools

Export citation

Search in Google Scholar

Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm

Proceedings article published in 2001 by H. K. Lam, S. H. Ling ORCID, Frank H. F. Leung, Peter K. S. Tam
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

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. ; Author name used in this publication: F. H. F. Leung ; Author name used in this publication: P. K. S. Tam ; Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering