• DocumentCode
    2990089
  • Title

    Discrete-time Neural Network Control for a Linear Induction Motor

  • Author

    Hernandez-Gonzalez, M. ; Sanchez, E.N. ; Loukianov, A.G.

  • Author_Institution
    CINVESTAV, Unidad Guadalajara, Guadalajara
  • fYear
    2008
  • fDate
    3-5 Sept. 2008
  • Firstpage
    1314
  • Lastpage
    1319
  • Abstract
    This paper presents a discrete-time control for a linear induction motor (LIM). First, an identifier is proposed with a nonlinear block controllable form (NBC) structure. This identifier is based on a discrete-time high order neural network trained on-line with an extended Kalman filter (EKF)-based algorithm. Then, a sliding mode control is used to achieve the purpose of tracking velocity and magnitude flux. The neural control performance is illustrated via simulations.
  • Keywords
    Kalman filters; discrete time systems; learning (artificial intelligence); linear induction motors; neurocontrollers; velocity control; discrete-time control; extended Kalman filter; linear induction motor; magnitude flux; neural network; nonlinear block control; velocity tracking; Control systems; Induction motors; Intelligent control; Neural networks; Nonlinear control systems; Nonlinear systems; Recurrent neural networks; Sliding mode control; Switching frequency; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 2008. ISIC 2008. IEEE International Symposium on
  • Conference_Location
    San Antonio, TX
  • ISSN
    2158-9860
  • Print_ISBN
    978-1-4244-2224-1
  • Electronic_ISBN
    2158-9860
  • Type

    conf

  • DOI
    10.1109/ISIC.2008.4635945
  • Filename
    4635945