• DocumentCode
    1899676
  • Title

    ANN-based feedback linearization for MIMO systems

  • Author

    Fattah, Hossam A. Abdel ; Sakr, Fattah Ahmed F ; Bahgat, Ahmed

  • Author_Institution
    Dept. of Electr. Power & Machines, Cairo Univ., Giza, Egypt
  • fYear
    1996
  • fDate
    15-18 Sep 1996
  • Firstpage
    289
  • Lastpage
    294
  • Abstract
    This paper addresses the problem of feedback linearization of nonlinear systems. The existing linearization methods require complete knowledge of the system model. A new method for feedback linearization, avoiding this requirement which is rarely satisfied in practice, is proposed. The method is based on artificial neural networks (ANNs). Simulation results show satisfactory performance when the proposed ANN-based feedback linearization is included in a tracking control system
  • Keywords
    MIMO systems; backpropagation; feedforward neural nets; linearisation techniques; neurocontrollers; nonlinear dynamical systems; robots; tracking; MIMO systems; backpropagation; feedback linearization; feedforward neural networks; nonlinear dynamical systems; robots; tracking control system; Artificial neural networks; Feedback; Jacobian matrices; MIMO; Neural networks; Neurofeedback; Nonlinear equations; State-space methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
  • Conference_Location
    Dearborn, MI
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-2978-3
  • Type

    conf

  • DOI
    10.1109/ISIC.1996.556216
  • Filename
    556216