摘要
在分析篦冷机主要性能和工作原理的基础上,根据篦冷机的工作特性,运用RBF神经网络建立控制模型,由寻优算法得到篦速来预测控制篦床压力。现场实际应用表明,RBF神经网络预测控制效果优于传统的PID控制。
According to diagnose the operating characteristics of grate cooler,control model was established by RBF Neural Network.The grate pressure was predicted and controlled by grate speed that was obtained from optimization algorithm.The practical application showed that the predictive Control effect of RBF Neural Network was better than traditional PID control.
出处
《水泥》
CAS
北大核心
2010年第10期58-60,共3页
Cement
关键词
预测控制
RBF
篦冷机
篦床压力
predictive Control
RBF
grate cooler
grate pressure First author＇s address： College of Electrical Engineering
Zhejiang University
Zhejiang
310027
China
