摘要
通过将RBF神经网络和常规PID控制器结合,提出了一种新的火电厂超临界机组过热汽温控制方案。将这种方法应用于主汽温控制,可以有效克服过热汽温对象的大滞后和大惯性,并能够克服对象在运行中参数变化的影响,获得良好的控制品质。仿真试验表明:所设计的系统在控制品质、鲁棒性方面明显优于常规PID控制系统。
By combining the RBF neural network with the general PID controller,a new superheated steam temperature control sys- tem is derived.This scheme can over the large delay and the uncertainty of superheated steam temperature object in supercritieal power unit.Through simulation in various situations,it validates that the control quality and the robustness of this control system ap- parently are superiors to the general PID system.
出处
《陕西电力》
2006年第6期10-12,共3页
Shanxi Electric Power
关键词
RBF神经网络
PID控制器
超临界机组
过热汽温
大迟廷
RBF neural network
PID controller
supercritical power unit
superheated steam temperature
large delay