• DocumentCode
    1131447
  • Title

    Asymptotic Tracking of Uncertain Systems With Continuous Control Using Adaptive Bounding

  • Author

    Stepanyan, Vahram ; Kurdila, Andrew

  • Author_Institution
    NASA Ames Res. Center, Mission Critical Technol. Inc., Moffett Field, CA, USA
  • Volume
    20
  • Issue
    8
  • fYear
    2009
  • Firstpage
    1320
  • Lastpage
    1329
  • Abstract
    This paper presents a robust adaptive control design method for a class of multiple-input-multiple-output uncertain nonlinear systems in the presence of parametric and nonparametric uncertainties and bounded disturbances. Using the approximation properties of the unknown continuous nonlinearities and the adaptive bounding technique, the developed controller achieves asymptotic convergence of the tracking error to zero, while ensuring boundedness of parameter estimation errors. The algorithm does not assume the knowledge of any bound on the unknown quantities in designing the controller. It is based on an integral technique involving the filtered tracking error and produces a continuous control. Theoretical developments are illustrated via simulation results.
  • Keywords
    MIMO systems; adaptive control; approximation theory; control nonlinearities; control system synthesis; convergence of numerical methods; filtering theory; neurocontrollers; nonlinear control systems; parameter estimation; robust control; tracking; uncertain systems; MIMO nonlinear uncertain system; adaptive bounding technique; asymptotic convergence; continuous nonlinearity; control signal; disturbance rejection; filtered tracking error; integral technique; multiple-input-multiple-output system; neural network approximation property; parameter estimation error; robust adaptive control design method; Asymptotic tracking; disturbance rejection; neural network approximation; nonlinear uncertain systems;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2009.2023214
  • Filename
    5161344