• DocumentCode
    3545227
  • Title

    Application of fuzzy PID control in polymerizing-kettle based on gray prediction model

  • Author

    Qi, Shufen ; Zhao, Chong

  • Author_Institution
    Dept. of Autom. Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
  • fYear
    2009
  • fDate
    16-19 Aug. 2009
  • Abstract
    The characteristic of the gray prediction control is less datum, poor information and small calculating amount, and the fuzzy inference rule has the characteristic of approximation linear function. Combined with the gray prediction and fuzzy PID control, a design method of fuzzy PID control algorithm based on gray prediction is presented. The method is applied polymerizing-kettle´s temperature control system, which has the performance of strong inertia, time-varying and uncertain long time-delay. The simulation results show that the control algorithm using fuzzy PID control based on gray prediction has the better performance than that of traditional PID control algorithm. It makes small overshooting, short adjusting time and good robustness, which is a effective method to improve polymerizing-kettle´s temperature control.
  • Keywords
    chemical industry; control system synthesis; delay systems; fuzzy control; polymerisation; predictive control; temperature control; three-term control; time-varying systems; uncertain systems; chemical industry; control design; fuzzy PID control; gray prediction control; polymerizing-kettle; strong inertia; temperature control system; time-varying system; uncertain long time-delay system; Design methodology; Fuzzy control; Inference algorithms; Linear approximation; Polymers; Predictive models; Robust control; Temperature control; Three-term control; Time varying systems; GM(1,1) model; fuzzy PID; gray predictive; polymerizing-kettle;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3863-1
  • Electronic_ISBN
    978-1-4244-3864-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2009.5274605
  • Filename
    5274605