Trajectory Tracking Control for an Underwater Vehicle Manipulator System Using a Neural-adaptive Network

A neural-adaptive trajectory tracking control strategy is proposed for an underwater vehicle manipulator system (UVMS). A feedback term based on a nominal dynamic model is used, and an adaptive neural network is utilized to approximate parametric uncertainties. The performance of this control scheme is demonstrated by applying it to a specific trajectory tracking task. The simulation results showed that the controller has a good performance under parametric uncertainty situations.