Model predictive formation control of multi-vessel systems considering ship-to-ship interaction

Abstract 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.

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Publication Details

Journal
Journal of Marine Science and Technology
Published
2026-04-11
DOI
https://doi.org/10.1007/s00773-026-01111-4
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Model predictive formation control of multi-vessel systems considering ship-to-ship interaction

Yusong Pang, Rudy R. Negenborn, Xin Xiong
Journal of Marine Science and Technology
Distributed Control Multi-Agent Systems
article

Model predictive formation control of multi-vessel systems considering ship-to-ship interaction

Yusong Pang, Rudy R. Negenborn, Xin Xiong
article en

Abstract

Abstract 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.

Journal of Marine Science and Technology
Openalex Percentile: Top 14%
Distributed Control Multi-Agent Systems
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