• DocumentCode
    2184643
  • Title

    Adaptive neural control of a class of MIMO nonlinear systems

  • Author

    Ge, Shuzhi S. ; Wang, Cong

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3530
  • Abstract
    In this paper, an adaptive neural control scheme is proposed for a class of uncertain MIMO nonlinear systems in block-triangular form. By exploiting the special structural property of the MIMO system, the developed scheme avoids the controller singularity problem completely without calculating the inverse of the estimated "decoupling matrix". Moreover, the stability of the whole closed-loop system is concluded in a nested iterative manner. The proposed scheme offers a systematic design procedure for the control of a class of uncertain MIMO nonlinear systems
  • Keywords
    MIMO systems; adaptive control; closed loop systems; neurocontrollers; nonlinear control systems; stability; MIMO nonlinear systems; adaptive control; block-triangular form; closed-loop system; neural control scheme; stability; uncertain systems; Adaptive control; Control systems; Couplings; Lyapunov method; MIMO; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Projection algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-7061-9
  • Type

    conf

  • DOI
    10.1109/.2001.980406
  • Filename
    980406