• DocumentCode
    2983912
  • Title

    The multi-objective controller adjustment using Ants system metaheuristic for non linear systems described by TS fuzzy models

  • Author

    Liouane, Hend ; Douik, Ali ; Messaoud, Hassani

  • Author_Institution
    Ecole Nat. d´´Ing. de Monastir (ATSI), Monastir, Tunisia
  • fYear
    2012
  • fDate
    2-4 July 2012
  • Firstpage
    86
  • Lastpage
    90
  • Abstract
    Artificial intelligence has attracted more and more attention in recent years. In this paper, we exploit essentially Ants System (AS) metaheuristic to adjust parameters of controller for non linear systems described by Takagi-Sugeno (TS) fuzzy models. The controller parameters are adjusted based on the desired performance set by the designer. Moreover, ants system metaheuristic was exploited to identify Pareto optimal solutions to find suitable trade-off between these performance criteria. An application example is presented to evaluate the competence of the proposed method.
  • Keywords
    Pareto optimisation; ant colony optimisation; fuzzy control; nonlinear control systems; AS metaheuristic; Pareto optimal solutions; TS fuzzy models; Takagi-Sugeno fuzzy models; ants system metaheuristic; artificial intelligence; multiobjective controller adjustment; nonlinear systems; Algorithm design and analysis; Biological system modeling; Optimization; PD control; Stability analysis; Vectors; Ants System metaheuristic; Controller adjustment; Non-linear systems; TS models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications (CIMSA), 2012 IEEE International Conference on
  • Conference_Location
    Tianjin
  • ISSN
    2159-1547
  • Print_ISBN
    978-1-4577-1778-9
  • Type

    conf

  • DOI
    10.1109/CIMSA.2012.6269613
  • Filename
    6269613