Skip to main navigation Skip to search Skip to main content

Design and stability analysis of fuzzy model-based nonlinear controller for nonlinear systems using genetic algorithm

  • H. K. Lam
  • , Hung Fat Frank Leung
  • , Peter K S Tam

Research output: Journal article publicationReview articleAcademic researchpeer-review

Abstract

This paper presents the stability analysis of fuzzy model-based nonlinear control systems, and the design of nonlinear gains and feedback gains of the nonlinear controller using genetic algorithm (GA) with arithmetic crossover and nonuniform mutation. A stability condition will be derived based on Lyapunov's stability theory with a smaller number of Lyapunov conditions. The solution of the stability conditions are also determined using GA. An application example of stabilizing a cart-pole typed inverted pendulum system will be given to show the stabilizability of the nonlinear controller.
Original languageEnglish
Pages (from-to)250-257
Number of pages8
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume33
Issue number2
DOIs
Publication statusPublished - 1 Apr 2003

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Fuzzy plant model
  • Genetic algorithm (GA)
  • Nonlinear controller
  • Nonlinear systems
  • Stability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • General Medicine
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Design and stability analysis of fuzzy model-based nonlinear controller for nonlinear systems using genetic algorithm'. Together they form a unique fingerprint.

Cite this