摘要
将预测控制和PID控制器结合运用于再热汽温系统的控制中。采用神经网络作为预测模型,并将混沌优化算法运用于该系统的PID参数在线优化。通过计算机仿真,验证了该算法的有效性。
The predictive control and the PID controller were combined for controlling of the reheated steam temperature system. The neural network was adopted as the predictive model, and the chaos optimization algorithm was used for on-line optimization of the PID parameters of the system. Computer simulations prove the algorithm effective.
出处
《华东电力》
北大核心
2007年第8期82-86,共5页
East China Electric Power
关键词
预测控制
PID
混沌优化
神经网络
再热汽温
predictive control
PID
chaos optimization
neural network
reheated steam temperature
作者简介
明学星（1978-），男，博士研究生，主要从事人工智能在热工过程中的应用。
