• DocumentCode
    1672963
  • Title

    A nonlinear control system using a fuzzy self tuning Grey predictor based on a PID controller

  • Author

    Kwan, Ahn Kyoung ; Van Quang, Duong ; Il, Yoon Jong

  • Author_Institution
    Sch. of Mech. & Automotive Eng., Univ. of Ulsan, Ulsan, South Korea
  • fYear
    2010
  • Firstpage
    418
  • Lastpage
    422
  • Abstract
    In this paper, a nonlinear control system using a fuzzy self tuning Grey predictor based on a PID controller is proposed. Firstly, the PID controller is designed according to the Zieger-Nichos 2 method with fast response and high robustness. Secondly, the grey predictor is suggested to use to estimate the system response in a near future in order to improve the control performance. In addition, the step of Grey predictor is adjusted by using the fuzzy control to satisfy the control requirement. Consequently, the control system fastens rising time, shortens settling time, reduces steady state error to zero, oppresses overshoot of transient response, and also prevents disturbance. A detailed specification of the control structure and its design process as well as simulation results achieved from Matlab/Simulink program are also presented. The simulation results show that the proposed control method has the ability to apply for nonlinear systems with higher control performance.
  • Keywords
    adaptive control; control system synthesis; fuzzy control; grey systems; nonlinear control systems; self-adjusting systems; three-term control; Matlab/Simulink program; PID controller; fuzzy control; fuzzy self tuning grey predictor; nonlinear control system; system response; Control systems; Mathematical model; Nonlinear systems; Predictive models; Simulation; Steady-state; Tuning; Grey predictor; PID controller; fuzzy self tuning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation and Systems (ICCAS), 2010 International Conference on
  • Conference_Location
    Gyeonggi-do
  • Print_ISBN
    978-1-4244-7453-0
  • Electronic_ISBN
    978-89-93215-02-1
  • Type

    conf

  • Filename
    5669782