Improved composite learning path-following control for the underactuated cable-laying ship via the double layers logical guidance

Abstract

This paper investigates the setpoints-based path-following issue of the underactuated cable-laying ship in the presence of the model uncertainty and unknown external disturbance. To implement the cable-laying task automatically, a novel double layers logical (DLL) guidance algorithm is proposed to generate the reasonable reference path for the cable and cable-laying vessel. In the first guidance layer, the reference path of the cable is programmed automatically by applying the logical guidance law. The path programming process is based on the given setpoints information and could be in accordance with the practical cable-laying requirement. Furthermore, the desired trajectory of the ship is derived in the second one by constructing the cable-related correlation equation. As for the control part, the improved composite learning algorithm is proposed to stabilize the error dynamics between the virtual ship and the actual ship. For merits of the robust neural damping technique, only two adaptive parameters are required to be updated online. That can lead to the computation superiority, which is significant for applying the proposed algorithm in the industrial process computer. The concise design could guarantee the ease-to-implementation of the theoretical algorithm in the practical engineering. Finally, much effort has been made to ensure that all signals in the closed-loop system are semi-global uniformly ultimately bounded (SGUUB). The numerical experiments are carried out to verify the effectiveness and superiority of the proposed algorithm, including the comparative experiment and the cable-laying experiment under the simulated ocean disturbance.