• DocumentCode
    2637322
  • Title

    Parameter conditions and least squares identification of single-input single-output convex fuzzy system

  • Author

    Kim, Tae-Wook ; Park, Sang Y. ; Lee, Jin S.

  • Author_Institution
    Pohang Univ. of Sci. & Technol., Pohang
  • fYear
    2007
  • fDate
    17-20 Sept. 2007
  • Firstpage
    568
  • Lastpage
    573
  • Abstract
    This paper presents fuzzy parameter conditions and a least squares (LS) based method to identify fuzzy systems that have convex input-output relationships. We first suggest sufficient conditions on parameters of zeroth order Takagi- Sugeno-Kang (TSK) type convex fuzzy systems and first order TSK-type convex fuzzy systems. By using the suggested conditions, we propose an LS based fuzzy system identification method whose system preserves the convexity property. Simulation results show that the proposed identification method preserves the convexity property and has less error than the conventional LS method.
  • Keywords
    control nonlinearities; fuzzy set theory; fuzzy systems; least squares approximations; multivariable systems; parameter estimation; convex input-output relationship; convexity property; least squares identification; parameter condition; single-input single-output convex fuzzy system; zeroth order Takagi-Sugeno-Kang system; Computer simulation; Fuzzy sets; Fuzzy systems; Least squares approximation; Least squares methods; Potential energy; Springs; Sufficient conditions; System identification; Takagi-Sugeno-Kang model; Takagi-Sugeno-Kang (TSK) fuzzy system; least squares; system identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE, 2007 Annual Conference
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-4-907764-27-2
  • Electronic_ISBN
    978-4-907764-27-2
  • Type

    conf

  • DOI
    10.1109/SICE.2007.4421047
  • Filename
    4421047