An Improved PID Neural Network Control Algorithm Based on Particle Swarm Optimization

被引：0

作者：

Dou, Chunhong ^{[1
]}

Zhang, Ling ^{[1
]}

机构：

[1] Weifang Univ, Sch Informat & Control Engn, Weifang, Shandong, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL I | 2011年

关键词：

PID; neural network; particle swarm algorithm; optimization;

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：

Aiming at the shortcomings of the weight value initially being randomly preset and easily immerging in the local minimum which usually exist in the PID neural network, the paper proposes an improved PM neural network based on the particle swarm optimization. To begin with, we utilize the particle swarm algorithm to optimize the initial weight value of PID neural network. Next, we successfully achieve the control strategy of a nonlinear coupling system using the improved PID neural network, and subsequently compare the control results with those obtained from the original PID neural network. The comparison indicates that the improved PID neural network base on the particle swarm optimization outperforms the original PID neural network in quickly achieving control strategy and improving the response speed.

引用

页码：32 / 34

页数：3