• DocumentCode
    3098596
  • Title

    Application of grey self-tuning fuzzy immune PID control for main steam temperature control system

  • Author

    Zhang, Yue ; Han, Pu ; Wang, Dong-feng ; Chen, Xiao-wei

  • Author_Institution
    Autom. Dept., North China Electr. Power Univ., Baoding, China
  • Volume
    1
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    588
  • Lastpage
    591
  • Abstract
    The prominent virtues of grey prediction are small information, few data and a little of computation. The conventional PID controller has strong robustness, sophisticated technology and simple structure, so it has been used widely in the process control. With the adjustable role of feedback response of biological immune systems, the capability of simulating non-linear functions with fuzzy rationalizing logic, and the advantage of gray prediction, an application of fuzzy immune PID control with gray prediction has been proposed. In view of the grey-step having great effect to the results of forecast, the fuzzy rules are used to adjust the forecast step, which is a very good supplement to the grey prediction. The method mentioned in this paper is applied to the main steam temperature control system of power plant, the simulation shows that this strategy has strong capability of anti-disturbance.
  • Keywords
    fuzzy control; grey systems; self-adjusting systems; steam plants; temperature control; three-term control; PID control; fuzzy rules; grey prediction; grey self-tuning fuzzy immune control; main steam temperature control; power plant; Biology computing; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Immune system; Process control; Robust control; Temperature control; Three-term control; Fuzzy immune PID control; Grey prediction; Prediction step; Steam temperature control system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212563
  • Filename
    5212563