• DocumentCode
    2261228
  • Title

    Solving Parameter Identification Problem of Nonlinear Systems Using Differential Evolution Algorithm

  • Author

    Wang, Ke ; Wang, Xiaodong ; Wang, Jinshan ; Jiang, Minlan ; Lv, Ganyun ; Feng, Genliang ; Xu, Xiuling

  • Author_Institution
    Dept. of Electron. Eng., Zhejiang Normal Univ., Jinhua
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    687
  • Lastpage
    691
  • Abstract
    A new technique, based on differential evolution algorithm, is proposed for solving the parameter identification problem of nonlinear systems. The technique improves the accuracy of parameter identification. Two kinds of process systems have been used as examples for demonstration. The effectiveness of differential evolution algorithm is compared with that of genetic algorithms in terms of obtained parameter accuracy and objective function value. The simulation results show that the accurate estimation of unknown system parameters and small values of objective function can be achieved by the proposed technique.
  • Keywords
    genetic algorithms; nonlinear systems; parameter estimation; differential evolution algorithm; genetic algorithms; nonlinear systems; parameter identification problem; Artificial intelligence; Artificial neural networks; Control engineering; Genetic algorithms; Information technology; Least squares methods; Nonlinear systems; Parameter estimation; Polynomials; System identification; Differential Evolution; Nonlinear Systems; Parameter Identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.556
  • Filename
    4739659