Adaptive backstepping neural network control of electro-hydraulic position servo system

Aiming at the electro-hydraulic servo system with mismatched uncertainties, an adaptive backstepping neural network position controller design is presented. By applying backstepping design strategy and online approaching uncertainties with RBF neural networks, a nonlinear controller for a hydraulic servo-system is developed based on Lyapunov stability theory, the problem of extreme expanded operation quantity is solved. Load, hydraulic cylinder and valve dynamics are incorporate in the design process. An adaptation law is also proposed to deal with uncertainties in hydraulic parameters and the electro-hydraulic shaker is taken as a testing example. Simulation and experiment investigations are provided to show the effectiveness of the proposed method.