Open AccessAdaptive sliding mode control of electro-hydraulic servo system based on RBF network
Author(s) -
Shuai Zhou,
H Wang,
J Li,
Linfeng Lan
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/784/1/012029
Subject(s) - control theory (sociology) , servomechanism , artificial neural network , computer science , compensation (psychology) , control engineering , adaptive control , servo , position (finance) , sliding mode control , engineering , control (management) , nonlinear system , artificial intelligence , physics , quantum mechanics , psychology , finance , psychoanalysis , economics
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.