Inverse Control of Nonlinear Servo System Based on Neural Networks

摘要

This paper presents an inverse controller based on neural networks for servo systems, and gives invertibility criterion for a class of nonlinear servo system. A feedforward multilayer neural network with closed-loop training schemes and Alopex weights learning algorithm is used to identify the inverse dynamic model of the servo system. The weights of the neural network is adjusted online by a feedback error learning method. Simulation results show that the method is effective in identification and control of servo system.