Existing studies on multi-vessel formations rarely combine physically based models of ship–ship hydrodynamic interaction with online formation control, so that energy benefits are typically assessed offline or only approximated through artificial potentials. This paper addresses this gap by embedding a reduced-order, hydrodynamics-aware resistance model into a hierarchical formation control framework for multi vessel systems. A three degree of freedom interaction model is incorporated into the cost function, enabling the supervisory controller to adaptively optimize inter ship spacing and formation geometry in a speed dependent and hydrodynamics aware manner. The lower level MPC ensures accurate trajectory tracking and stability under the guidance of the top level optimization. Four simulation studies are conducted to evaluate the proposed method. The platooning formation is first analyzed as a reference, followed by the triangular formation, which achieves balanced tracking performance and stability. The echelon formation is then examined, demonstrating significant energy savings in medium to high speed regimes while maintaining yaw stability. Finally, an unconstrained optimization scenario is explored, where the system autonomously adapts its geometry without prescribed patterns, revealing emergent energy efficient and stable arrangements across different speed ranges. Results show that the proposed approach not only reduces resistance and improves energy efficiency but also enhances formation adaptability and robustness under varying operating conditions. These findings provide new insights into hydrodynamics aware cooperative control and the development of energy conscious fleet management strategies for future maritime transportation. ... Read more

Autonomous surface vessels are increasingly expected to operate cooperatively in future waterborne transport systems, where multiple vessels can sail in coordinated formations to improve safety, efficiency, and operational capability. However, when vessels operate in close proximity, ship-to-ship hydrodynamic interactions become non-negligible. These interactions influence maneuvering dynamics, tracking performance, formation stability, and propulsion energy demand. Conventional formation control methods often treat such interactions as external disturbances or ignore them entirely, which limits their applicability to energy-efficient and interaction-sensitive multi-vessel operations. This thesis addresses this gap by developing hydrodynamics-aware model predictive formation control methods for energy-efficient multi-vessel systems.

The thesis first reviews cooperative formation control strategies, communication structures, hydrodynamic interaction mechanisms, and formation-resistance characteristics for autonomous surface vessels. Based on this synthesis, a conceptual framework is proposed in which ship-to-ship interactions are not only treated as disturbances to be compensated, but also as predictable physical couplings that can be exploited for energy-aware formation design. An interaction-aware model predictive control framework is then developed for multi-vessel formation tracking. A three-degree-of-freedom vessel model is combined with a data-informed ship-to-ship interaction model, allowing surge, sway, and yaw interaction effects to be incorporated into the prediction and control process. Simulation studies demonstrate that explicitly considering interaction forces improves tracking robustness and provides a more realistic basis for formation control in close-spacing regimes.

Building on this interaction-aware control foundation, the thesis further investigates hydrodynamics-aware formation optimization for reducing fleet-level energy consumption. A hierarchical control architecture is designed, where an upper-level decision layer optimizes formation configuration and reference speed based on interaction-aware energy indicators, while a lower-level model predictive controller tracks the resulting references under vessel dynamics and actuator constraints. Different formation layouts, including tandem, triangular, echelon, and adaptive configurations, are examined to reveal the trade-offs between energy saving, formation tracking accuracy, and stability. The results show that energy-efficient formations are strongly speed- and geometry-dependent, and that favorable hydrodynamic interaction regions can be used to reduce resistance and propulsion demand.

Finally, the thesis extends the framework to route-following operations under environmental disturbances. A leader–follower MPC structure with disturbance estimation is proposed to improve post-turn spacing recovery and maintain interaction-favorable geometries under wind, current, and sea-state-related energy effects. Compared with centralized MPC, the leader–follower formulation keeps the fleet more persistently in energy-saving regimes. In the studied route scenario, the LF-MPC architecture achieves a mission-average energy-consumption index of −4.17%, whereas the centralized MPC case results in a positive average index of +1.28%. These findings indicate that hydrodynamics-aware formation control can provide additional energy-saving potential beyond conventional single-vessel optimization, while preserving formation tracking performance and operational feasibility.

Overall, this thesis contributes a systematic framework for integrating ship-to-ship hydrodynamic interactions into model predictive formation control. It demonstrates that interaction-aware prediction, configuration optimization, and hierarchical control can jointly support energy-efficient, robust, and adaptable multi-vessel operations. The results provide a foundation for future research on scalable distributed control, propulsion-inclusive energy optimization, and real-world deployment of cooperative autonomous vessel formations. ... Read more

The formation control of autonomous surface vessels presents significant challenges when operating in close proximity, where ship-to-ship interaction becomes non-negligible. While conventional formation control methods often neglect these interactions or simplify them excessively, this paper develops a centralized model predictive control (MPC) framework that explicitly incorporates a three-degrees-of-freedom interaction model. This interaction model is constructed empirically based on existing computational fluid dynamics results, offering an efficient and practical way to approximate proximity-induced forces in real-time. The proposed control strategy enables accurate trajectory tracking and effective disturbance adaptation in typical formation geometries, including platooning, parallel, and triangular formations. Simulation results demonstrate that the MPC controller can outperform traditional PID controllers in both tracking precision and interaction robustness across the configurations. Formation-specific performance differences are also analyzed in detail. ... Read more