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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