• DocumentCode
    1924632
  • Title

    The Boiler-Turbine Coordinated Control System Based on Immune Feedback Mechanism

  • Author

    Peng, Dao-gang ; Zhang, Hao ; Yang, Ping

  • Author_Institution
    Shanghai Univ. of Electr. Power, Shanghai
  • Volume
    1
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    449
  • Lastpage
    453
  • Abstract
    The boiler-turbine coordinated control system in power station has the characteristics of multi-variables, nonlinear, time-varying, coupling and large time-delay etc, and the performance of the boiler-turbine control system has great impact on the safety and economy of a power unit. Biology immune system is characterized by its strong robustness and self-adaptability even when encountering amounts of disturbances and uncertain conditions. To overcome the effects of nonlinear behavior and coupling of energy feed-demand for boiler-turbine coordinated control system, prompted by the regulation rule of biology immune feedback mechanism, aiming at a class of 160 MW nonlinear boiler-turbine system model, a control strategy for boiler-turbine coordinated system based on immune feedback mechanism is presented in this paper. Simulation results for different loads of boiler-turbine system show that the control strategy has a better decouple and disturbance rejection ability.
  • Keywords
    boilers; feedback; nonlinear control systems; robust control; self-adjusting systems; turbines; biology immune system; boiler-turbine coordinated control system; decouple rejection ability; disturbance rejection ability; energy feed-demand; immune feedback; nonlinear behavior; power station; robustness; self-adaptability; Biological control systems; Biological system modeling; Control system synthesis; Control systems; Couplings; Feedback; Immune system; Nonlinear control systems; Power generation; Time varying systems; Boiler-turbine; Coordinated control system; Immune PID control; Immune feedback mechanism;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370186
  • Filename
    4370186