• DocumentCode
    3526556
  • Title

    Discrete-time adaptive learning control for parametric uncertainties with unknown periods

  • Author

    Miao Yu ; Deqing Huang

  • Author_Institution
    Dept. of Biotechnol. & Chem. Technol., Aalto Univ., Aalto, Finland
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    1786
  • Lastpage
    1791
  • Abstract
    In this paper, we approach the problem of unknown periods for a class of discrete-time parametric nonlinear systems with nonlinearities which do not necessarily satisfy the sector-bounded condition. The unknown periods hide in the parametric uncertainties, which is difficult to estimate. By incorporating a logic-based switching mechanism, we estimate the period and bound of unknown parameter simultaneously under Lyapunov-based analysis. Rigorous proof is given to demonstrate that a finite number of switchings can guarantee the asymptotic regulation of the nonlinear system considered. The simulation result also shows the efficacy of the proposed switching periodic adaptive control method.
  • Keywords
    Lyapunov methods; adaptive control; control nonlinearities; discrete time systems; iterative methods; learning systems; nonlinear control systems; parameter estimation; periodic control; time-varying systems; uncertain systems; Lyapunov-based analysis; asymptotic nonlinear system regulation; discrete-time adaptive learning control; discrete-time parametric nonlinear systems; logic-based switching mechanism; nonlinearities; parametric uncertainties; switching periodic adaptive control method; unknown parameter bound estimation; unknown parameter period estimation; unknown periods; Nickel; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760141
  • Filename
    6760141