• DocumentCode
    2303184
  • Title

    Research on RBF tuning PID and fuzzy immune control system of superheat temperature

  • Author

    Xue, Yang ; Yan, ZhenJie

  • Author_Institution
    Fac. of Electr. & Autom. Eng., Shanghai Univ. of Electr. Power, Shanghai, China
  • Volume
    7
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    3528
  • Lastpage
    3531
  • Abstract
    The main steam temperature control system is necessary to ensure high efficiency and high load-following capability in the operation of modern power plant, which has the characteristics of large inertia, long time-delay and time-varying, etc. Thus conventional PID control strategy cannot achieve good control performance. Prompted by the feedback regulation mechanism of biology immune response and neural network, a composite control strategy based on RBF tuning PID and fuzzy immune control is presented in this paper. It has stronger robustness and better self-adaptive ability, which can be adaptive to the change in the parameters of the controlled plant. A simulation study of the main steam temperature control system shows that this control strategy is effective, practicable and superior to conventional PID control.
  • Keywords
    adaptive control; fuzzy control; robust control; self-adjusting systems; steam plants; temperature control; three-term control; RBF tuning PID control system; fuzzy immune control system; power plant; robustness; self-adaptive ability; steam temperature control system; superheat temperature; Artificial neural networks; Immune system; Power generation; Radial basis function networks; Temperature control; Tuning; RBF neural network; fuzzy control; immune control; superheat temperature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5584089
  • Filename
    5584089