RBF Neural Network Control of Electric Servo System Based on LMI and Disturbance Observer
In order to improve the loading force tracking accuracy of the electric servo system,a system of disturbance observer and controller is designed based on linear matrix inequality(LMI).Aimed at the nonlinear factors in the system,the RBF neural network is used to approximate the mathematical model of the system.Based on the establishment of the system tracking target model,the disturbance observer is designed according to LMI to compensate the excess force of the controller,and the Lyapunov function is applied to prove the convergence of disturbance observer and controller.A simulation model is constructed in MATLAB/Simulink,and the accurate estimation of the corresponding quantities of the system by the disturbance observer and RBF neural network is conducted under different working conditions,which shows that the errors all meet the set performance indicators,and the control performance of the proposed control strategy is better compared with PID control.
electric serv systemlinear matrix inequalitydisturbance observerRBF neural network
万方数据
维普
