• DocumentCode
    1751477
  • Title

    Adaptive critic based neuro-observer

  • Author

    Liu, Xin ; Balakrishnan, S.N.

  • Author_Institution
    Dept. of Mech. & Aerosp. Eng. & Eng. Mech., Missouri Univ., Rolla, MO, USA
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1616
  • Abstract
    A new Neural Network (NN) based observer design method for nonlinear systems represented by nonlinear dynamics and linear/nonlinear measurement is proposed in this paper. In this new approach, as the first step, the observer design problem is changed into a ´controller´ design problem by establishing the error dynamics, and then the Adaptive Critic (AC) based approach is applied on this error dynamics to design a ´controller´, such that the errors are driven to zero. The resulting observer has inherent robustness from the AC based design approach. Some simulations are presented to illustrate the effectiveness of this approach
  • Keywords
    neural nets; nonlinear control systems; observers; Adaptive Critic; controller design; neuro-observer; nonlinear systems; observer design; Aerodynamics; Control systems; Cost function; Design methodology; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Observers; Recurrent neural networks; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2001. Proceedings of the 2001
  • Conference_Location
    Arlington, VA
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-6495-3
  • Type

    conf

  • DOI
    10.1109/ACC.2001.945958
  • Filename
    945958