摘要
提出一种基于RBF辨识神经网络算法的神经网络PID控制方案,由RBF网络对系统进行在线辨识,建立其在线参考模型并为PID控制器提供了梯度信息,从而实现控制器参数的在线调整。仿真结果表明,该控制方法应用于真空炉温度控制时控制精度高,动态特性好,收到了良好的效果。
A PID control method based on RBF neural network algorithm is put forward by realizing on-line identification with RBF network. Setting up on-line reference model and offering gradient information for PID controller, the on-line adjustment of the controller＇s parameter will be accomplished. The simulating result indicates that the method has higher precision and better dynamic characteristic when it is used in vacuum furnace＇s temperature controlling system.
出处
《湖南工业大学学报》
2007年第3期39-41,共3页
Journal of Hunan University of Technology
基金
湖南省教育厅基金资助项目(06D077)
关键词
RBF神经网络
PID控制
在线辨识
仿真
Radial basis function neural network
PID control
on-line identification
simulating
