Neural Network Tracking Control of Ocean Surface Vessels with Input Saturation

In this paper, robust adaptive tracking control is proposed for ocean surface vessels based on neural network. In the tracking control design, parametric uncertainties, unknown disturbances and input saturation are explicitly considered. Using neural network (NN) approximation and backstepping control techniques, full state feedback control and output feedback control are investigated to tackle system uncertainties and control input saturation. An auxiliary design system is presented to analyze the effect of input saturation, and states of auxiliary design system are utilized to develop the tracking control. Under the both of developed tracking control approaches, semi-global uniform boundedness of all closed-loop signals are guaranteed via Lyapunov analysis. Simulation studies are given to illustrate the effectiveness of the proposed tracking control.