• DocumentCode
    1661189
  • Title

    Iterative Learning Control for 2-D linear discrete systems with Roessor´s model

  • Author

    Fan Wu ; Xiao-Dong Li

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China
  • fYear
    2012
  • Firstpage
    464
  • Lastpage
    467
  • Abstract
    Almost all existing Iterative Learning Control (ILC) methods are specifically designed for the one-dimensional dynamical systems. And many two-dimensional dynamical systems are often required to do repeatable works in engineering fields. This paper presents a novel P-type ILC rule for the two-dimensional systems represented by Roessor´s model. The proof on convergence of the proposed ILC rule is based on the solution formula of the two-dimensional Roessor´s model in ILC process. By transferring the ILC tracking errors into a one-dimensional system in iteration direction, the convergence condition of the proposed ILC rule is derived.
  • Keywords
    discrete systems; iterative methods; linear systems; neurocontrollers; 2D linear discrete systems; ILC methods; P-type ILC rule; Roessor model; iterative learning control; Convergence; Eigenvalues and eigenfunctions; Iterative methods; Manipulators; Process control; Vectors; 2-D linear discrete systems; Iterative learning control; Roessor´s model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4673-1871-6
  • Electronic_ISBN
    978-1-4673-1870-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2012.6485203
  • Filename
    6485203