Cooperative dynamic positioning of multiple offshore vessels with persistent ocean disturbances via iterative learning

Unlike the traditional dynamic positioning of single offshore vessel, this paper considers the cooperative dynamic positioning (CDP) of multiple offshore vessels with persistent ocean disturbances induced by wind, waves and ocean currents, for the purpose of collectively holding a relative formation and reaching a reference position. The dynamic surface control (DSC) design technique combined with an iterative learning approach is proposed to devise the adaptive CDP controllers. The presented algorithm guarantees that a relative formation among vehicles can be achieved if the graph induced by the vessels and the reference point contains a spanning tree. Lyapunov analysis demonstrates that all signals in the closed-loop system are uniformly ultimately bounded, and dynamic positioning errors converge to a small neighborhood of origin by suitably choosing the design parameters. Simulation results validate the efficacy of the proposed controller.