Journal of Liaoning Petrochemical University

Journal of Liaoning Petrochemical University ›› 2010, Vol. 30 ›› Issue (2): 58-61.DOI: 10.3696/j.issn.1672-6952.2010.02.016

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PID Control of Double Inverted Pendulum Based on RBF Neural Network

WANG Hong-nan   

  1. School of Information and Control Engineering, Liaoning Shihua University,Fushun Liaoning113001, P.R.China
  • Received:2010-01-20 Published:2010-06-25 Online:2017-07-05

基于RBF神经网络二级倒立摆系统的PID控制

王宏楠   

  1. 辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001
  • 作者简介:王宏楠(1981-),男,辽宁辽阳市,硕士。

Abstract:  

A method of PID control based on RBF neural network for double inverted pendulum was proposed. The parameters of PID controller are tuned by RBF network, so can achieve a optimal controller, and realize the stability control for double inverted pendulum. The simulation results show that it has higher accuracy, faster response and smaller overshot. The proposed method has better control effect for the multi-variable, nonlinear and fast system.

Key words: Double inversed pendulum , RBF neural network , PID control

摘要: 针对二级倒立摆系统,提出一种基于RBF神经网络的PID控制方法。该方法采用RBF神经网络对
PID控制器的参数进行优化修正,从而使控制器处于最优状态,实现二级倒立摆的稳定控制。仿真结果表明,该方法
的控制精度较高,响应迅速,超调量较小。对于多变量、非线性、不稳定的快速系统,具有较好的控制效果。

关键词: 二级倒立摆 ,  , RBF神经网络 ,  , PID控制

Cite this article

WANG Hong-nan. PID Control of Double Inverted Pendulum Based on RBF Neural Network[J]. Journal of Liaoning Petrochemical University, 2010, 30(2): 58-61.

王宏楠. 基于RBF神经网络二级倒立摆系统的PID控制[J]. 辽宁石油化工大学学报, 2010, 30(2): 58-61.