Electro-hydraulic Servo System Modeling And Control Strategy Studies

Electro-hydraulic servo system is a typical nonlinear time-varying system. Traditional control methods can't obtain satisfactory control effect in some area with high precision and much interference. Adaptive control has the good robustness because adaptive control can adjust the system parameters automatically to ensure good control effect depending on the system status and neural network has a good ability to map the nonlinear function and self-learning. Neural network adaptive control can often obtain better control effect in nonlinear system, combining the advantages of the adaptive control and neural network, because neural network could use to replace the identification and controller in adaptive control aimed to adjust the controller parameters rapidly.The paper made some researches on intelligent control strategy in electro-hydraulic servo system, based on the electro-hydraulic servo system of a mine sweeping plough in a weapon system. Firstly, on the basis of analysis of system works and characteristics, the paper researches on neural network identification technology for establishing dynamic model of system with RBF(Radial Basis Function) neural network, secondly, the paper designed a self-tuning control system based on neural network, and made a performance test of the control system on the co-simulation platform of AMESim and Matlab/Simulink. Simulation results showed that the control strategy can minimize stable state error of system, enhanced the adaptive ability and anti-disturbance ability of the system, and met control request of system.