摘要
本文设计了基于DE优化的RBF神经网络与DE优化改进的PID算法相结合的控制系统,利用优化后的RBF神经网络预测加压泵压力,结合Labview、MATLAB、step7混合编程,使用优化后的RBF神经网络与在线PID算法控制PLC,完成了优化流程,采用误差指标J等于网络的预测误差进行优化。结果表明,本文提出的控制系统能提高鲁棒性、缩小超调量、加速响应、改善出水水质。
This paper designs a control system that combines RBF neural network based on DE optimization and PID algorithm improved by DE optimization.The optimized RBF neural network is used to predict the pressure of the booster pump,and combined with Labview,MATLAB,and step7 hybrid programming,the optimized RBF neural network and online PID algorithm are implemented to control the PLC.The optimization process is completed,and the error index J is used to equal the prediction error of the network for optimization.The results indicate that the control system proposed in thispaper can improve robustness,reduce overshoot,accelerate response,and improve effluent quality.
作者
王斌
WANG Bin(College of Intelligent Manufacturing Engineering,Shanxi Institute of Science and Technology,Jincheng,Shanxi 048000,China)
出处
《自动化应用》
2023年第24期29-31,34,共4页
Automation Application
关键词
智能算法
神经网络
DE算法
intelligence algorithm
neural network
DE algorithm
