Dynamic Load Positioning for Subsea Installation via Adaptive Neural Control

Abstract

In this paper, positioning control is investigated for the installation of subsea systems, with attached thrusters, under time-varying irrotational ocean current. Backstepping in combination with adaptive feedback approximation techniques is employed in the design of the control, with the option of high-gain observer for output feedback control. The stability of the design is demonstrated through Lyapunov analysis where semiglobal uniform boundedness of the closed-loop signals is guaranteed. The proposed adaptive neural control is able to capture the dominant dynamic behaviors without exact information on the hydrodynamic coefficients of the structure and current measurements. Comparative simulations with linear proportional derivative (PD), PD with adaptive term, and model-based controls are carried out. The proposed technique is found to be effective and robust and reduces tracking error of the subsea module.