• DocumentCode
    1163022
  • Title

    On initial conditions in iterative learning control

  • Author

    Xu, Jian-Xin ; Yan, Rui

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
  • Volume
    50
  • Issue
    9
  • fYear
    2005
  • Firstpage
    1349
  • Lastpage
    1354
  • Abstract
    Initial conditions, or initial resetting conditions, play a fundamental role in all kinds of iterative learning control methods. In this note, we study five different initial conditions, disclose the inherent relationship between each initial condition and corresponding learning convergence (or boundedness) property. The iterative learning control method under consideration is based on Lyapunov theory, which is suitable for plants with time-varying parametric uncertainties and local Lipschitz nonlinearities.
  • Keywords
    Lyapunov methods; adaptive control; convergence; iterative methods; learning systems; Lyapunov theory; boundedness property; initial resetting condition; iterative learning control; learning convergence; local Lipschitz nonlinearity; time-varying parametric uncertainty; Computer errors; Control nonlinearities; Control systems; Convergence; Iterative algorithms; Iterative methods; Robustness; System performance; Trajectory; Uncertainty; Initial conditions; iterative learning control (ILC); learning convergence;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2005.854613
  • Filename
    1506941