• DocumentCode
    467671
  • Title

    Optimizing Parameters of Fuzzy Controller Based on Genetic Algorithm

  • Author

    Liu, Chao-ying ; Wang, Hui-fang ; Song, Xue-ling ; Song, Zhe-ying ; Li, Kai

  • Author_Institution
    Hebei Univ. of Sci. & Technol., Shijiazhuang
  • Volume
    1
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    413
  • Lastpage
    418
  • Abstract
    For effects of the parameters of fuzzy controller with nonlinear scaling factors on a system´s performance and the parameters are interactive, this paper proposes a method based on genetic algorithm (GA) to tune and optimize the parameters. Simulation results show that system which adopted the parameters derived from the method has better dynamics and static property. When the parameters or structure of plant is changed, a fuzzy controller with nonlinear scaling factors can maintain good performance indicators through re-tuning parameters and has stronger robustness.
  • Keywords
    fuzzy control; genetic algorithms; fuzzy controller; genetic algorithm; nonlinear scaling factors; optimizing parameters; parameters tuning; Control systems; Cybernetics; Fuzzy control; Fuzzy systems; Genetic algorithms; Machine learning; National electric code; Nonlinear control systems; Optimization methods; Steady-state; Fuzzy control; Genetic algorithm; Nonlinear scaling factors; Parameters tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370180
  • Filename
    4370180