• DocumentCode
    575324
  • Title

    Discussion of stability of learning type neural network direct controller and its folding behavior

  • Author

    Yamada, Takayuki

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Ibaraki Univ., Hitachi, Japan
  • fYear
    2012
  • fDate
    20-23 Aug. 2012
  • Firstpage
    459
  • Lastpage
    464
  • Abstract
    This paper discusses stability of a learning type neural network direct controller in the viewpoint of its folding behavior. First, I discuss the stability for the nonlinear plant and the nonlinear neural network. This discussion confirms that we can include the plant Jacobian problem into the tuning problem of the parameter determining the neural network convergence speed because of the folding behavior. Next, I simulate the learning type neural network direct controller using a sine wave as an object plant. This simulation results well match with the result of the stability discussion.
  • Keywords
    learning systems; neurocontrollers; nonlinear control systems; stability; folding behavior; learning type neural network direct controller; neural network convergence speed; nonlinear neural network; nonlinear plant; object plant; plant Jacobian problem; sine wave; stability; tuning problem; Biological neural networks; Cost function; Equations; Jacobian matrices; Mathematical model; Stability analysis; Adaptive; Controller; Learning; Neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE Annual Conference (SICE), 2012 Proceedings of
  • Conference_Location
    Akita
  • ISSN
    pending
  • Print_ISBN
    978-1-4673-2259-1
  • Type

    conf

  • Filename
    6318483