• DocumentCode
    2262174
  • Title

    Fuzzy system identification using rule-based models

  • Author

    Shaout, A.K. ; McDonough, J.T., III

  • Author_Institution
    Michigan Univ., Dearborn, MI, USA
  • fYear
    1993
  • fDate
    16-18 Aug 1993
  • Firstpage
    510
  • Abstract
    The purpose of the paper was to examine the methods used to develop fuzzy models of SISO systems which may be thought of as “rule-based” using non-recursive techniques. First, we look at the mathematical concepts used to develop the models. Second, special constraints used in the creation of the fuzzy models are specified. Third, fuzzy models of a simple linear system are developed. The models are used to determine the effects of incorrect or overparameterization on the effects of the model performance. Finally, fuzzy models of a simple non-linear system are developed and their performance examined
  • Keywords
    fuzzy control; fuzzy systems; identification; knowledge based systems; linear systems; nonlinear systems; SISO systems; fuzzy system identification; linear system; model performance; nonlinear system; nonrecursive techniques; overparameterization; rule-based models; Biological system modeling; Control system synthesis; Equations; Fuzzy sets; Fuzzy systems; Linear systems; Mathematical model; Predictive models; System testing; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
  • Conference_Location
    Detroit, MI
  • Print_ISBN
    0-7803-1760-2
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1993.343008
  • Filename
    343008