Modeling and Simulation of PID Networked Control Systems Based on Neural Network

Authors

Zhanzhi Qiu, 1. Mechanical Engineering Inst, Dalian Jiaotong University, Dalian 116028, China; ;2. Software Technology Inst, Dalian Jiaotong University, Dalian 116028, China;
Shifeng Li, 1. Mechanical Engineering Inst, Dalian Jiaotong University, Dalian 116028, China; ;

Abstract

Abstract: According to the problems of the delay compensation and PID parameters tuning of networked control systems, a class of rapid PID networked control systems based on improved BP network was proposed. Considering the problems of obtaining hidden layer nodes number and local optimum of the BP network delay prediction model, a calculation method was proposed to obtain hidden layer nodes number, and an improved genetic algorithm was proposed to train the BP network. Considering the problems of integral saturation, parameters tuning and model mismatch of the PID network control systems, a PID parameter adjuster was designed based on on-line BP network. The simulation results show that this system has the advantage of rapid running speed, coping model mismatch, and good control performance with random short delay or random long delay.

Recommended Citation

Qiu, Zhanzhi and Li, Shifeng (2019) "Modeling and Simulation of PID Networked Control Systems Based on Neural Network," Journal of System Simulation: Vol. 30: Iss. 4, Article 26.
DOI: 10.16182/j.issn1004731x.joss.201804026
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss4/26

First Page

1423

Revised Date

2016-11-11

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201804026

Last Page

1432

CLC

TP391.9

Recommended Citation

Qiu Zhanzhi, Li Shifeng. Modeling and Simulation of PID Networked Control Systems Based on Neural Network[J]. Journal of System Simulation, 2018, 30(4): 1423-1432.

DOI

10.16182/j.issn1004731x.joss.201804026