Robust Adaptive Position Mooring Control for Marine Vessels

TLDR

The paper proposes a robust adaptive control with dynamic allocation for positioning marine vessels with thruster‑assisted mooring, addressing parametric uncertainties, unknown disturbances, and input nonlinearities. The control strategy employs neural‑network approximation, variable‑structure techniques, backstepping, and Lyapunov synthesis, with full‑state and observer‑based output feedback, and dynamic allocation to handle uncertainties, saturation, and dead‑zone effects, validated by numerical simulations. The proposed controller guarantees semi‑global uniform boundedness of all closed‑loop signals.

Abstract

In this paper, robust adaptive control with dynamic control allocation is proposed for the positioning of marine vessels equipped with a thruster assisted mooring system, in the presence of parametric uncertainties, unknown disturbances and input nonlinearities. Using neural network approximation and variable structure based techniques in combination with backstepping and Lyapunov synthesis, the positioning control is developed to handle the uncertainties, input saturation and dead-zone characteristics of the mooring lines and thrusters. Full state feedback with all states measurable and output feedback using high gain observer to estimate unmeasurable states are considered. Dynamic control allocation is presented for actuation of the position mooring system. Under the proposed robust adaptive control, semi-global uniform boundedness of the closed-loop signals are guaranteed. Numerical simulations are carried out to show the effectiveness of the proposed control.