• DocumentCode
    315932
  • Title

    An optimised fuzzy logic controller

  • Author

    Chan, P.T. ; Rad, A.B. ; Tsang, K.M.

  • Author_Institution
    Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, Hong Kong
  • Volume
    2
  • fYear
    1997
  • fDate
    1-5 Jul 1997
  • Firstpage
    975
  • Abstract
    An optimal fuzzy logic controller (FLC) tuning algorithm is reported in this paper. With the aid of genetic algorithms (GA), optimal rules of a fuzzy logic controller are designed. This is achieved by deriving a tailor-made encoding scheme, initialisation, crossover and mutation of rule table into chromosomes. The genetic algorithm incorporates as much existing knowledge of the system as possible to increase the speed of optimisation. For a linear system, the proposed algorithm shows a significant improvement in convergence. For a nonlinear system, the algorithm attempted the truck and truck-and-tailer backing up problems for the whole plan. It is concluded that the proposed algorithm can be applied effectively to solve variety of problems and can accommodate different performance criterion
  • Keywords
    fuzzy control; genetic algorithms; linear systems; nonlinear control systems; optimal control; chromosomes; crossover; genetic algorithms; initialisation; linear system; mutation; nonlinear system; optimal fuzzy logic controller; optimal rules; performance criterion; rule table; speed of optimisation; tailor-made encoding scheme; truck backing up problem; truck-and-tailer backing up problems; tuning algorithm; Algorithm design and analysis; Biological cells; Convergence; Encoding; Fuzzy logic; Genetic algorithms; Genetic mutations; Linear systems; Nonlinear systems; Optimal control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
  • Conference_Location
    Barcelona
  • Print_ISBN
    0-7803-3796-4
  • Type

    conf

  • DOI
    10.1109/FUZZY.1997.622841
  • Filename
    622841