• DocumentCode
    300861
  • Title

    Function approximation by fuzzy systems

  • Author

    Lewis, F.L. ; Zhu, S.Q. ; Liu, K.

  • Author_Institution
    Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA
  • Volume
    5
  • fYear
    1995
  • fDate
    21-23 Jun 1995
  • Firstpage
    3760
  • Abstract
    This paper provides an overview of our recent work on function approximation by fuzzy systems. Some scalar definitions in fuzzy logic control (FLC) are extended to the n-dimensional case, including the vector fuzzy number and membership vector. A mathematical expression is given for the function g(x) manufactured by a fuzzy system. It is shown that, under suitable assumptions, the fuzzy associative memory function g(x) is Lipschitz and approximates arbitrarily closely on compact set any specified continuous function. Relations are given between the accuracy of the approximation and the number of membership functions selected in each dimension. A major role is played in the analysis by the notion of the `convex combination´, which considerably simplifies the analysis compared to other approaches in the literature
  • Keywords
    approximation theory; content-addressable storage; function approximation; fuzzy control; fuzzy set theory; fuzzy systems; Lipschitz; convex combination; function approximation; fuzzy associative memory; fuzzy logic control; fuzzy systems; membership functions; membership vector; n-dimensional case; vector fuzzy number; Additives; Associative memory; Automatic control; Function approximation; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Manufacturing; Robotics and automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, Proceedings of the 1995
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2445-5
  • Type

    conf

  • DOI
    10.1109/ACC.1995.533841
  • Filename
    533841