• DocumentCode
    2419693
  • Title

    Fuzzy Modeling for Nonlinear System with Structured Data Uncertainty

  • Author

    Ding, Haishan ; Mao, Jianqin

  • Author_Institution
    Beijing Univ. of Aeronaut. & Astronaut., Beijing
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1812
  • Lastpage
    1816
  • Abstract
    In this paper, a new fuzzy modeling method with structured data uncertainty is proposed for nonlinear systems. The new robust modeling criterion, which aims to minimize the worst-case residual error, is formulated. The algorithm to obtain the approximate solutions of modeling problems under the new criterion is given in consideration of data uncertainty with a known structure. The new method is superior to the existing nonlinear modeling approaches. The advantages of the new method are illustrated by simulation results.
  • Keywords
    data structures; fuzzy set theory; fuzzy systems; nonlinear systems; uncertainty handling; fuzzy modeling; nonlinear system; structured data uncertainty; worst-case residual error; Binary trees; Fuzzy sets; Fuzzy systems; Inference algorithms; Modeling; Nonlinear systems; Parameter estimation; Robustness; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2006 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9488-7
  • Type

    conf

  • DOI
    10.1109/FUZZY.2006.1681951
  • Filename
    1681951