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

doi:10.16182/j.issn1004731x.joss.201804026

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.

Key words: networked control systems, delay predication, PID control, BP network, genetic algorithm

CLC Number:

TP391.9

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.

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