Research on Neural Network Backstepping Adaptive Control Algorithm for Electro-Hydraulic Servo System
摘要
An adaptive backstepping control algorithm combined with RBF neural network is proposed for the control problem of electro-hydraulic servo system caused by factors such as nonlinearity and parameter uncertainty. Firstly, the complex high-order nonlinear electro-hydraulic servo system is decomposed into a low-order simple system with backstepping method. And the control law with unknown nonlinear function term is obtained. Secondly, the RBF neural network is applied to approximate the nonlinear function terms in the control law, and the adaptive rate is designed using the Lyapunov stability analysis method. Finally, simulation verification is conducted on the built Simulink simulation model, and the simulation results show that the adaptive control algorithm based on the RBF neural network backstepping method can achieve tracking control of the given signal and meet the desired dynamic performance criteria. In addition, in order to deal with the sensor noise problems that may be encountered in the actual deployment, the first-order filtering algorithm is introduced and verified in the simulation, which effectively reduces the noise interference.