This thesis presents a thorough study into the development and implementation of a control method for autonomous unmooring, trajectory tracking and mooring on an autonomous model-scale vessel.
Mooring and unmooring are vital processes in the operation of ships, as it is the system that secures and releases a ship to a terminal or multiple terminals. The process has remained relatively identical over the years, whereas autonomous shipping has been researched over time. This study addresses the lack of focus given to autonomous mooring and unmooring by offering a control strategy that leverages the vessel’s thrusters to perform these tasks, along with trajectory tracking. The study begins by reviewing existing research on trajectory tracking and maritime vessel mooring/unmooring, revealing the gaps in the integration of both procedures within autonomous operations.

To overcome these challenges, the study selects an applicable mathematical model for the vessel which will be controlled. This model covers kinematic and kinetic elements, as well as actuation and thruster allocation. This sets the groundwork for the development of a control strategy capable of precisely predicting and tracking the vessel’s position during unmooring, and trajectory tracking and mooring. Model Predictive Control (MPC) was chosen as an ideal control approach due to its ability to predict future states and effectively handle the complexities of marine operations. MPC makes it ideal for the difficulties of mooring and unmooring, where precise control is necessary to ensure safety and efficiency.

The control strategy was then developed and implemented in MATLAB/Simulink, with the approach modified to meet the model-scale vessel’s specific dynamics and operational requirements.
In addition, Key Performance Indicators (KPIs) to assess the effectiveness of the strategy were introduced. The strategy’s performance was assessed in three operational phases: unmooring, trajectory tracking, and mooring. The results show that the MPC controls the vessel’s trajectory well, with errors staying well below acceptable bounds. The largest deviation of the final trajectory during the mooring test was 9.8% of the length of the ship. A 1.0% deviation for the benchmark trajectories could also be observed. These results, in addition to others, validate the suggested strategy’s accuracy and dependability in practical situations.

In summary, this thesis provides a comprehensive control approach for autonomous unmooring, trajectory tracking and mooring for an autonomous model-scale vessel, bridging the gap between theoretical study and implementation in simulation. While the research identifies several limitations that present the potential for additional study, it also lays a solid foundation for future developments in autonomous maritime technology.