• DocumentCode
    3485263
  • Title

    Elevator group control system tuned by a fuzzy neural network applied method

  • Author

    Imasaki, Naoki ; Kubo, Susumu ; Nakai, Shoji ; Yoshitsugu, Tatsuo ; Kiji, Jun-Ichi ; Endo, Tsunekazu

  • Author_Institution
    Syst. & Software Eng. Lab., Toshiba Corp., Kawasaki, Japan
  • Volume
    4
  • fYear
    1995
  • fDate
    20-24 Mar 1995
  • Firstpage
    1735
  • Abstract
    We have developed a high-performance elevator group control system with a performance tuning function, which employs a fuzzy neural network as a performance forecasting model of the elevator system. The fuzzy neural network, which is a structured neural network based on a fuzzy reasoning framework, stores the correlation between control-parameters and the response of the elevator group as a fuzzy rule set. It performs a fuzzy rule-based reasoning to forecast the system performance of the elevator group. The performance tuning function utilizes the forecasting model in order to search the optimal control parameters which give the best system performance in the present traffic situation. The fuzzy neural network applied system can automatically adapt itself to various traffic situations. This paper gives the overview of the elevator group control system with the fuzzy neural network and shows the validity of the methodology by some simulation results
  • Keywords
    adaptive control; fuzzy control; fuzzy neural nets; inference mechanisms; intelligent control; knowledge based systems; lifts; optimal control; adaptive control; elevator group control system; fuzzy neural network; fuzzy rule set; fuzzy rule-based reasoning; optimal control; performance forecasting model; performance tuning function; Communication system traffic control; Control system synthesis; Control systems; Elevators; Fuzzy control; Fuzzy neural networks; Fuzzy reasoning; Predictive models; System performance; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int
  • Conference_Location
    Yokohama
  • Print_ISBN
    0-7803-2461-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.1995.409916
  • Filename
    409916