Abstract

ABSTRACT This paper investigates the synchronization control problem for a supply vessel during underway replenishment with unknown dynamics, unknown disturbances, input saturation and unavailable velocities. A virtual trajectory shifted by a distance at an angle relative to the trajectory of the supplied vessel is planned. A high-gain observer observer is employed to estimate unavailable vessel velocities and an auxiliary design system is constructed to address the effect of input saturation. Then, the adaptive radial basis function neural networks are employed to approximate unknown dynamics and the adaptive laws are derived to estimate bounds of unknown disturbances. Incorporating the above into the dynamic surface control method, an output feedback robust adaptive neural synchronization control law is developed to force the supply vessel to track the virtual trajectory such that the synchronization navigation between the supply and the supplied vessels is realized. The theoretical analysis and simulation results validate our developed control scheme.

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