• DocumentCode
    1702576
  • Title

    Fuzzy logic and genetic algorithm technique for non-liner system of overhead crane

  • Author

    Petrenko, Yury N. ; Alavi, Seyed Enayatollah

  • Author_Institution
    Belarusian Nat. Tech. Univ., Minsk, Belarus
  • fYear
    2010
  • Firstpage
    848
  • Lastpage
    851
  • Abstract
    This paper presents an improved fuzzy logic controller technique parameters estimation, based on genetic algorithm. It is kwon, that fuzzy control rules for a control system is always built by designers with trial and error and based on their experience on some preliminary experiments. We use a genetic algorithm (GA) based methods to generate a satisfactory fuzzy rule base spontaneously. The proposed method with GA produces a fuzzy rules base with smaller number of rules and given proper location of the consequent singletons. Digital simulation results are provided for a control system of overhead crane.
  • Keywords
    cranes; fuzzy control; fuzzy set theory; genetic algorithms; nonlinear control systems; parameter estimation; digital simulation; fuzzy logic controller; fuzzy rule; genetic algorithm; nonlinear system; overhead crane; parameter estimation; Artificial intelligence; Cranes; Fuzzy logic; Fuzzy sets; Genetics; Mathematical model; Search problems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Technologies in Electrical and Electronics Engineering (SIBIRCON), 2010 IEEE Region 8 International Conference on
  • Conference_Location
    Listvyanka
  • Print_ISBN
    978-1-4244-7625-1
  • Type

    conf

  • DOI
    10.1109/SIBIRCON.2010.5555013
  • Filename
    5555013