Design and Experimental Verification of Electro-hydraulic Position Servo Control System
The electro-hydraulic position servo system has the problems of external disturbance and nonlinearity.This paper designs a control system for the electro-hydraulic position servo system based on sensitivity analysis(SA)and particle swarm optimization(PSO)for the radial basis function(SAPSO-RBF)neural network.The SAPSO-RBF neural network is used to estimate the unknown parameters in the servo system model,and a sliding mode controller for the servo system is designed.An experimental setup for the dual output symmetrical hydraulic cylinder electro-hydraulic position servo system is constructed.The proposed SAPSO-RBF neural network sliding mode control and traditional sliding mode control are experimentally verified.The experimental results show that the SAPSO-RBF neural network sliding mode control method has higher tracking accuracy,higher robustness,and effectively suppresses the system's chattering.
electro-hydraulic position servo control systemsensitivity analysisparticle swarm optimizationsliding mode controllerexperimental device design
万方数据
维普
