电厂过热汽温神经PID控制系统的仿真研究

针对火电厂主汽温被控对象的大迟延、模型不确定性,设计了基于RBF神经网络的神经PID汽温控制系统,并对控制系统进行仿真试验,其仿真结果表明了设计的控制器具有良好的位置跟随性、抗干扰性和鲁棒性.;In order to overcome the large delay and the uncertainty of the main-stream temperature object in fossil-fired power station, a neural PID temperature control system based on RBF neural network is proposed. It contains two neural netwoks: system-online identifier and neural PID controller. The simulation results show that the designed system has good position tracking propery, adaptability to overcome disturbances and robustness