Application of PID Control Based on RBF Neural Network in Electro-Hydraulic Servo System for Steel Strip Deviation

Abstract

The working principle of the electrical-hydraulic servo system for steel strip deviation is introduced. The mathematical model of the system is established, and the performance indexes in time domain are analyzed with MATLAB. Aiming at the steel strip deviation, an improved PID control method based on RBF neural network is proposed. According to Jacobian information identification of RBF neural network combined with incremental PID algorithm, the self-tuning of parameters is implemented so that the performance of the system can achieve the designed requirements. Compared with traditional PID control, the simulation results show RBF- PID control has better dynamic performance and stabilization.