Adaptive sliding mode control of electro-hydraulic servo system based on RBF network

Abstract

Abstract In order to solve the steady-state error in position tracking control for electro-hydraulic servo universal testing machine, caused by uncertain parameters in the system model, an adaptive sliding mode control strategy based on RBF neural network is proposed for this situation. This paper utilizes the adaptive ability of RBF neural network to improve the control quality of the electro-hydraulic position servo system. The strategy has three parts: the equivalent control, the reaching law control and the compensation control based on RBF network. Simulations verify that the control system can track the reference curve well with unknown parameters.