• DocumentCode
    2159543
  • Title

    A fast iterative learning control scheme for linear time-variant continuous systems

  • Author

    Deyuan Meng ; Yingmin Jia ; Junping Du ; Shiying Yuan

  • Author_Institution
    Seventh Res. Div., Beihang Univ. (BUAA), Beijing, China
  • fYear
    2007
  • fDate
    2-5 July 2007
  • Firstpage
    3883
  • Lastpage
    3890
  • Abstract
    In this paper, a fast iterative learning control (ILC) scheme is presented for linear time-variant continuous systems. It ensures that the whole desired output trajectory can be accurately tracked only after one learning trial. In this scheme, there are two types of ILC laws, i.e., the time-variant D-type ILC law and the fast ILC law. Based on two-dimensional (2-D) model, convergence of the both types of ILC laws is proved respectively, and sufficient conditions are derived. Motivated by this, two corresponding algorithms for ILC are proposed, which enable us to find the desired control inputs. Meanwhile, the 2-D linear continuous-discrete Roesser´s type model is developed by extending the applications of ILC from time-invariant control systems to time-variant control systems. Two numerical simulation examples are included to illustrate the obtained results.
  • Keywords
    continuous systems; discrete systems; iterative learning control; linear systems; time-varying systems; 2D linear continuous-discrete Roesser type model; ILC scheme; fast ILC law; fast iterative learning control scheme; linear time-variant continuous systems; sufficient conditions; time-variant D-type ILC law; time-variant control systems; Algorithm design and analysis; Continuous time systems; Convergence; Equations; Mathematical model; Trajectory; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2007 European
  • Conference_Location
    Kos
  • Print_ISBN
    978-3-9524173-8-6
  • Type

    conf

  • Filename
    7068496