• DocumentCode
    1639845
  • Title

    An approach for dynamical adaptive fuzzy modeling

  • Author

    Cerrada, M. ; Aguilar, J. ; Colina, E. ; Titli, A.

  • Author_Institution
    Dept. Sistemas de Control, Los Andes Univ., Merida, Venezuela
  • Volume
    1
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    156
  • Lastpage
    161
  • Abstract
    In this work, an approach for the development of adaptive fuzzy models is presented. The approach allows to incorporate the system dynamics into the fuzzy membership functions which are defined in terms of a dynamic function with adjustable parameters. These parameters are adapted using a gradient descent based algorithm. Some application examples to illustrate the performance of the dynamical adaptive fuzzy models on system identification are presented
  • Keywords
    adaptive systems; fuzzy set theory; gradient methods; identification; modelling; adjustable parameters; dynamic function; dynamical adaptive fuzzy modeling; fuzzy membership functions; gradient descent based algorithm; system identification; Adaptive systems; Artificial neural networks; Automatic control; Design methodology; Equations; Fuzzy logic; Fuzzy sets; Fuzzy systems; Supervised learning; System identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7280-8
  • Type

    conf

  • DOI
    10.1109/FUZZ.2002.1004978
  • Filename
    1004978