Embedded Model Predictive Control for ship path tracking under environmental disturbances via MMG-Fossen model fusion

It is evident that discrepancies in ship navigation can result in many consequences, harming navigational safety, economic efficiency, and environmental sustainability. Such consequences may include groundings, collisions, augmented fuel consumption, and extended voyage distances. These outcomes are frequently attributable to adverse marine ecological factors, with wind, waves, and currents exerting the most significant influence. To address this issue, the present paper proposes a solution that utilizes the Maneuvering Motion Group (MMG) model as a force-coupling constraint and designs an Embedded Model Predictive Control (E-MPC). This methodology has been demonstrated to reduce forces and moments acting on the vessel in the sway and yaw directions, whilst concomitantly increasing forces in the surge direction. The Fossen three-degree-of-freedom model is employed as the vessel motion model. It is embedded within MPC constraints to perform online rolling optimization of vessel motion, thereby fully leveraging its predictive advantages. In conjunction with linear interpolation, the second-order Nomoto model facilitates the direct conversion of vessel control variables into rudder angle and engine speed. Furthermore, the present study employed measured data from a 28,000 DWT bulk carrier navigating severe sea conditions for comparative simulation.