• DocumentCode
    1956945
  • Title

    Conditions for general Mamdani fuzzy controllers to be nonlinear

  • Author

    Ying, Hao

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wayne State Univ., Detroit, MI, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    201
  • Lastpage
    203
  • Abstract
    Fuzzy controllers are best used as nonlinear controllers although they can be linear, piecewise linear or nonlinear. Currently, there exist no theoretical methods to determine whether a fuzzy controller is nonlinear. Because a fuzzy controller has many degrees of freedom in terms of its components selection (e.g., input fuzzy sets, output fuzzy sets, and fuzzy rules), linear controllers can be unconsciously and undesirably generated. In the present paper, we establish conditions under which nonlinearity of a general class of Mamdani fuzzy controllers can be determined. These fuzzy controllers can use input fuzzy sets of any types, arbitrary fuzzy rules, arbitrary singleton output fuzzy sets, arbitrary inference methods, Zadeh fuzzy logic AND operator, and the centroid defuzzifier. We prove that the fuzzy controllers using Zadeh AND operator are always nonlinear, regardless of choice of the other components. The general fuzzy controllers using the product AND operator are also always nonlinear except when all input fuzzy sets are triangular or trapezoidal and a couple of other conditions are satisfied. The exceptions lead to piecewise linear or linear controllers.
  • Keywords
    controllers; fuzzy control; fuzzy logic; nonlinear control systems; Zadeh fuzzy logic AND operator; arbitrary fuzzy rules; arbitrary inference methods; arbitrary singleton output fuzzy sets; centroid defuzzifier; components selection; fuzzy controller; fuzzy rules; general Mamdani fuzzy controllers; input fuzzy sets; nonlinear controllers; output fuzzy sets; product AND operator; Couplings; Fuzzy control; Fuzzy logic; Fuzzy sets; Input variables; Piecewise linear techniques; Shape; Sliding mode control; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2002. Proceedings. NAFIPS. 2002 Annual Meeting of the North American
  • Print_ISBN
    0-7803-7461-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2002.1018055
  • Filename
    1018055