Adaptive PID Control Strategy for Nonlinear Model Based on RBF Neural Network

被引：0
|
作者：
Liu, Changliang [1 ]
Ming, Fei [1 ]
Ma, Gefeng [1 ]
Ma, Junchi [2 ]
机构：
[1] N China Elect Power Univ Baoding, Dept Control Theory & Control Engn, Baoding 071003, Peoples R China
[2] Jianbi Power Plant China Guodian Corp, Zhenjiang 212006, Peoples R China
来源：
AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION | 2012年 / 137卷
关键词：
RBF neural network; PID controller; nonlinear system; SYSTEMS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As the actual industrial processss are nonlinear, time-varying, large delay and uncertain, it is difficult to establish accurate mathematical model, As a result, it is impossible to get good control effect with conventional PID controller. In this paper we put forward a new method of compound control based on RBF neural network and PID. This method only need we give the sketchy PID controller parameters, the neural network makes the optimal adjustment to the PID controller parameters, and gains the good control performance finally. Simulation results indicate that with the proposed controller the adaptability, strong robustness and satisfactory control performance are superior to those of the conventional PID controller in the nonlinear and time-varying system.
引用
收藏
页码：529 / +
页数：2
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