• DocumentCode
    354194
  • Title

    Sliding mode control of nonlinear system based on neural networks

  • Author

    Hongli, Lei ; Dianzhi, Zhang ; Wenhua, Liu

  • Author_Institution
    Air Force Coll. of Eng., Xi´´an, China
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    962
  • Abstract
    In order to minimize the information needed from a plant, an adaptive sliding mode control scheme for a nonlinear plant without any model is proposed based on strong robust sliding mode control with the favorable approximation ability of basis function neural nets. The global stability of the control system is proved by theoretical analysis. Simulation shows the strong robustness and feasibility of the control scheme
  • Keywords
    adaptive control; asymptotic stability; neurocontrollers; nonlinear control systems; radial basis function networks; robust control; variable structure systems; adaptive sliding mode control scheme; approximation ability; basis function neural nets; global stability; strong robustness; Neural networks; Nonlinear systems; Sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
  • Conference_Location
    Hefei
  • Print_ISBN
    0-7803-5995-X
  • Type

    conf

  • DOI
    10.1109/WCICA.2000.863376
  • Filename
    863376
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=354194