• DocumentCode
    2602692
  • Title

    An observer based adaptive PID controller

  • Author

    Yao, Leehter ; Wen, Hong-Kang

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taipei Univ. of Technol., Taipei, Taiwan
  • fYear
    2011
  • fDate
    26-29 June 2011
  • Firstpage
    511
  • Lastpage
    516
  • Abstract
    An Adaptive Fuzzy PID Controller with Genetic Algorithm (GA) to tune its parameters is proposed in this paper. The task of the controller is to track the trajectory of a nonlinear system as best as it could. The Lyapunov´s direct method is used as a tool for nonlinear system analysis and design. In which, the Lyapunov´s linearization method is proven here to be useful for linear control. The paper relies on linearization method and the direct method to formulate its stability theory. The controller has two states, a learning state and a controlling state where GA performs on-line tuning of the controller´s parameters. The GA method has the effect of tuning PID parameters to meet operation time constraint and system performance. In the controlling state, there are a supervisory controller designed to ensure system stability and a compensator appended to compensate for modeling error and disturbance. Overall performance of the controller is not compromised by the fact that it has only three parameters to work with.
  • Keywords
    Lyapunov methods; adaptive control; control system synthesis; genetic algorithms; linear systems; nonlinear control systems; observers; three-term control; GA; Lyapunov direct method; Lyapunov linearization method; PID parameters; adaptive fuzzy PID controller; controlling state; genetic algorithm; learning state; linear control; nonlinear system; nonlinear system analysis; nonlinear system design; observer; stability theory; supervisory controller design; Adaptive systems; Biological cells; Genetic algorithms; Nonlinear systems; Observers; Trajectory; Tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling, Identification and Control (ICMIC), Proceedings of 2011 International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/ICMIC.2011.5973758
  • Filename
    5973758