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
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;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
DOI :
10.1109/ROBIO.2014.7090680