Stable fuzzy controller design for uncertain nonlinear systems: Genetic algorithm approach

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

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

2 Citations (Scopus)


This paper addresses the stable fuzzy controller design problem of nonlinear systems. The methodology is based on a fuzzy logic approach and the genetic algorithm (GA). In order to analyze the system stability, the TSK fuzzy plant model is employed to describe the dynamics of the nonlinear plant. A fuzzy controller is then developed to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the GA. An application example on stabilizing an inverted pendulum system will be given. Simulation and experimental results will be presented to verify the applicability of the proposed approach.
Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Number of pages6
Publication statusPublished - 11 Jul 2003
EventThe IEEE International conference on Fuzzy Systems - St. Louis, MO, United States
Duration: 25 May 200328 May 2003


ConferenceThe IEEE International conference on Fuzzy Systems
Country/TerritoryUnited States
CitySt. Louis, MO

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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