• DocumentCode
    3493733
  • Title

    Controller design using parametric neural networks

  • Author

    HashemiNejad, M. ; Murata, J. ; Hirasawa, K.

  • Author_Institution
    Dept. of Electr. Eng., Kyushu Univ., Fukuoka, Japan
  • fYear
    1995
  • fDate
    26-28 Jul 1995
  • Firstpage
    1275
  • Lastpage
    1280
  • Abstract
    A neural network (NN) of a more flexible internal structure than usual is used to design a better controller. A parametric NN (PNN) can represent both linear and nonlinear relationships explicitly and simultaneously by setting its parameters appropriately. In many cases we have some information about the system which enable us to build a linear controller for it. But of course this is not enough for treating nonlinear plants. Using PNN we could make a complimentary linearized controller and then, after starting the learning, in an online manner it will be extended to a nonlinear dominant controller
  • Keywords
    control system synthesis; neurocontrollers; nonlinear control systems; complimentary linearized controller; controller design; flexible internal structure; nonlinear dominant controller; parametric neural networks; Artificial intelligence; Control systems; Control theory; Electrical equipment industry; Error correction; Linear systems; Neural networks; Nonlinear control systems; Nonlinear equations; Nonlinear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE '95. Proceedings of the 34th SICE Annual Conference. International Session Papers
  • Conference_Location
    Hokkaido
  • Print_ISBN
    0-7803-2781-0
  • Type

    conf

  • DOI
    10.1109/SICE.1995.526694
  • Filename
    526694