• DocumentCode
    476188
  • Title

    The study on a new intelligent control model ICM-LG and its application to the inverted pendulum

  • Author

    Liu, Li

  • Author_Institution
    Dept. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding
  • Volume
    4
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    2424
  • Lastpage
    2429
  • Abstract
    An intelligent control model ICM-LG which inherits the advantages of linear quadratic regulator (LQR), human-imitating intelligent control theory and genetic algorithm is proposed in this paper. ICM-LG is independent of the accuracy of the controlled systempsilas mathematical model, neednpsilat analyze physical properties and control rules of system in detail, and avoids the pre-configuring control parameters and secondary manual regulation. By optimizing parameters with the unequal weights, the control process can reflect that the different control sub-targets have different priorities, and that the control demand can be focused on rapidity or stability differently. The stable control experiments for the inverted pendulum and the compares to LQR and the human-imitating intelligent control method show the validity and advantage of ICM-LG.
  • Keywords
    genetic algorithms; intelligent control; linear quadratic control; nonlinear control systems; pendulums; stability; ICM-LG; genetic algorithm; human-imitating intelligent control theory; intelligent control model; inverted pendulum; linear quadratic regulator; mathematical model; parameters optimisation; stable control experiments; Control system synthesis; Control systems; Cybernetics; Genetic algorithms; Intelligent control; Machine learning; Mathematical model; Nonlinear control systems; Optimal control; Regulators; Genetic algorithm; Human-imitating intelligent control; ICM-LG; Linear quadratic regulator; The inverted pendulum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620813
  • Filename
    4620813