• DocumentCode
    2273221
  • Title

    Combined adaptive and fuzzy control using multiple models

  • Author

    Xu, Jian-Xin ; Liu, Chen ; Hang, Chang C.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
  • fYear
    1994
  • fDate
    26-29 Jun 1994
  • Firstpage
    22
  • Abstract
    This paper presents a control strategy to deal with processes in which both system parameters and orders are unknown and undergo abrupt structural variations. To handle such complicated control problems, a combined adaptive and fuzzy control scheme is developed. A number of generalized minimum variance (GMV) controllers are designed according to all the possible process structures. A higher level model selection mechanism decides which controller candidate is the best. A fuzzy modification algorithm is introduced to improve the system responses in transient period by detuning the control weights of GMV controllers. To cope with possible instability caused by non-minimum phase dynamics, a fuzzy PID backup is introduced as well. Some adaptation is added to the fuzzy PID backup to obtain better system performance
  • Keywords
    control system synthesis; dynamics; fuzzy control; model reference adaptive control systems; three-term control; adaptive control; fuzzy PID backup; fuzzy control; fuzzy modification algorithm; generalized minimum variance controllers; instability; model selection mechanism; multiple models; nonminimum phase dynamics; Adaptive control; Control system synthesis; Control systems; Fuzzy control; Fuzzy systems; Optimal control; Programmable control; System performance; Three-term control; Weight control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1896-X
  • Type

    conf

  • DOI
    10.1109/FUZZY.1994.343694
  • Filename
    343694