Artificial Potential-Based Adaptive ${{H}_{\infty }}$ Synchronized Tracking Control for Accommodation Vessel

Combining with artificial potential field and robust H
_∞
methods, the neural network (NN)-based adaptive synchronized tracking control is proposed for accommodation vessel (AV). The control task is to drive AV synchronous tracking floating production storage and offloading (FPSO). For finishing the task, NN is employed to approximate the unknown nonlinear dynamics of AV; H
_∞
method is to guarantee the system states of AV robust to exogenous disturbances; artificial potential method aims to produce the attractive and repulsive forces to assist AV maintaining desired distance with FPSO so that the gangway connecting both AV and FPSO is operated smoothly. Finally, it is proven that the proposed control scheme can guarantee that all error signals of the tracking control are Semi-Globally Uniformly Ultimately Bounded (SGUUB) and AV can synchronously track FPSO to desired accuracy. The simulation results further demonstrate the effectiveness of the proposed method.