Adaptive Neural Network Saturation Compensation in Motion Control Systems

A neural network-based saturation compensation signal is inserted into the actuator control, effectively preventing it from being saturated. The proposed neural network (NN) saturation compensation scheme presents a form of intelligent anti-windup saturation where NN adjusts its output to prevent saturation of the control signal. On-line weights tuning law, the overall closed-loop performance, and the boundedness of the NN weights are derived and guaranteed based on the Lyapunov approach. The actuator saturation is assumed to be unknown, and the compensator is inserted into a feedforward path. The simulation results indicate that the proposed scheme can effectively compensate for the saturation nonlinearity in the presence of system uncertainty