• DocumentCode
    304100
  • Title

    A predictive fuzzy relational controller

  • Author

    Bourke, Mary M. ; Fisher, D.G.

  • Author_Institution
    Dept. of Chem. Eng., Alberta Univ., Edmonton, Alta., Canada
  • Volume
    2
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    1464
  • Abstract
    The fuzzy controller proposed in this paper has the same structure as a conventional model-based predictive controller but uses a relational-based model which is superior to rule-based models in that it: permits numerical and analytical analysis; employs the max-product compositional operator which gives better results, using a minimum distance criterion than the traditional max-min compositional operator; and includes self learning (fuzzy identification) capabilities. Simulation results show that this fuzzy controller gives better performance than a gain-scheduled PI (proportional plus integral) controller when applied over the full operating range of a continuous nonlinear process
  • Keywords
    fuzzy control; continuous nonlinear process; fuzzy identification; max-product; minimum distance criterion; predictive fuzzy relational controller; relational-based model; self learning; Adaptive control; Feedback; Filters; Fuzzy control; Optimal control; PD control; Pi control; Predictive control; Predictive models; Proportional control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.552391
  • Filename
    552391