• DocumentCode
    169767
  • Title

    Polynomial Model of the Inverse Plant ILC Algorithm

  • Author

    Songjun, Mutita

  • Author_Institution
    Fac. of Eng., Naresuan Univ., Phitsanulok, Thailand
  • fYear
    2014
  • fDate
    6-9 May 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper the new iterative learning control algorithm is proposed and its properties are derived. An important characteristic of the algorithm is that they use the polynomial representations of the inverse plant G to construct the new control law. The approach is based on the parameter optimization through a quadratic performance index which its solution will convert in norm to zero. It is capable to produce an improvement to the convergence rate. As the number of polynomial term increases, faster convergence rate is accomplished and the ideal plant inverse algorithm is approached. A comparison between the proposed algorithm and the inverse type parameter optimal ILC is also presented based significantly on the convergence rate.
  • Keywords
    convergence of numerical methods; iterative methods; learning systems; performance index; polynomials; inverse plant ILC algorithm polynomial model; inverse plant polynomial representations; inverse type parameter optimal ILC; iterative learning control algorithm; parameter optimization; quadratic performance index; Approximation algorithms; Approximation methods; Convergence; Mathematical model; Optimization; Polynomials; Robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2014 International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4799-4443-9
  • Type

    conf

  • DOI
    10.1109/ICISA.2014.6847447
  • Filename
    6847447