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

H. K. Lam, S. H. Ling, Hung Fat Frank Leung, P. K S Tam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Pages908-911
Number of pages4
Publication statusPublished - 1 Dec 2001
Event10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia
Duration: 2 Dec 20015 Dec 2001

Conference

Conference10th IEEE International Conference on Fuzzy Systems
CountryAustralia
CityMelbourne
Period2/12/015/12/01

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

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