• DocumentCode
    291332
  • Title

    A learning algorithm of fuzzy rules using GA for MRACS with time-delay

  • Author

    Shida, Koichiro ; Ochia, H. ; Fujikawa, Hideji ; Yamada, Shin´ichi

  • Author_Institution
    Musashi Inst. of Technol., Tokyo, Japan
  • Volume
    2
  • fYear
    1994
  • fDate
    5-9 Sep 1994
  • Firstpage
    1387
  • Abstract
    By use of fuzzy reasoning, MRACS can be applied to nonlinear systems. Genetic algorithms can be used to get optimal control rules automatically. These rules are remarkably better than hand-constructedones, but the optimizing procedure is time-consuming. In this paper, we try three techniques to simplify the adaptive rules and obtain quasi-optimal parameters rapidly
  • Keywords
    control system synthesis; delays; fuzzy control; genetic algorithms; learning systems; model reference adaptive control systems; nonlinear control systems; optimal control; MRACS; fuzzy reasoning; fuzzy rules; genetic algorithms; learning algorithm; nonlinear systems; optimal control rules; time-delay; Adaptive control; Automatic control; Design methodology; Fuzzy control; Fuzzy reasoning; Genetic algorithms; Nonlinear systems; Process design; Programmable control; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, Control and Instrumentation, 1994. IECON '94., 20th International Conference on
  • Conference_Location
    Bologna
  • Print_ISBN
    0-7803-1328-3
  • Type

    conf

  • DOI
    10.1109/IECON.1994.397997
  • Filename
    397997