• DocumentCode
    3587075
  • Title

    PID neural network decoupling control of deaerator pressure and water level control system

  • Author

    Peng Wang ; Hao Meng ; Qingzhou Ji

  • Author_Institution
    Coll. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2014
  • Firstpage
    2298
  • Lastpage
    2303
  • Abstract
    The deaerator pressure and deaerator water level are intercoupling in marine steam power plant. Traditional PID control strategy is difficult to get satisfactory control effect. We must take corresponding decoupling measures. This paper proposes a deaerator pressure and deaerator water level decoupling control strategy based on PID neural network, with which we can make comprehensive utilization of the advantage of both PID and neural network. Results of the simulation show that compared with traditional PID control strategy, the PID neural network decoupling control strategy can provide more stability and faster response speed in deaerator pressure and deaerator water level control.
  • Keywords
    level control; marine power systems; neurocontrollers; pressure control; steam power stations; three-term control; PID neural network decoupling control strategy; deaerator pressure decoupling control strategy; deaerator water level decoupling control strategy; decoupling measures; marine steam power plant; water level control system; Artificial neural networks; Biological neural networks; Level control; Mathematical model; Neurons; Valves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ROBIO.2014.7090680
  • Filename
    7090680