Automatic rule tuning of a fuzzy logic controller using particle swarm optimisation

Gu Fang, Ngai Ming Kwok, Dalong Wang

Research output: Chapter in Book / Conference PaperChapter

2 Citations (Scopus)

Abstract

While fuzzy logic controllers (FLCs) are developed to exploit human expert knowledge in designing control systems, the actual establishment of fuzzy rules and tuning of fuzzy membership functions are usually a time consuming exercise. In this paper a technique, based on the particle swarm optimisation (PSO), is employed to automatically tune the fuzzy rules of a Mamdani-type of fuzzy controller. The effectiveness of the designed controller is demonstrated by the control performance of such an FLC to a nonlinear water tank system with process time delay. The results are compared favourably to a PSO tuned PID controller.
Original languageEnglish
Title of host publicationArtificial Intelligence and Computational Intelligence
EditorsFu Lee, Wang Hepu, Deng Yang Gao, Jingsheng Lei
Place of PublicationGermany
PublisherSpringer-Verlag
Pages326-333
Number of pages8
ISBN (Print)3642165265
Publication statusPublished - 2010

Keywords

  • fuzzy logic
  • mathematical optimization.

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