Abstract
This paper considers cooperative dynamic positioning (CDP) of multiple offshore vessels in the presence of dynamical uncertainties, time-varying ocean disturbances and unmeasured velocity, aimed at collectively holding a relative formation and reaching a reference position. K-filter observers are first designed to estimate the unmeasured velocity information of each vessel, and then observer based CDP controllers are developed with the aid of dynamic surface control (DSC) technique, neural network and iterative learning approach. The formation among vehicles can be guaranteed if the graph induced by the vessels and the reference point contains a spanning tree. It is proved by Lyapunov analysis that the proposed control laws can ensure that all the signals in the closed-loop systems are uniformly ultimately bounded, and tracking errors converge to a small neighborhood of origin.
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