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Phased Predictive Berthing Control in Low-Speed Maneuvering for Autonomous Inland Ships

delete2026-06-03
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PRE
AI
C
Chenguang Liu
B
B Y Liu
W
Wenxiang Wu
张国庆 (Guoqing Zhang)
L
Lang Xiao
DOI:10.1109/joe.2026.3685148delete
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Abstract

Abstract

En 中文
To address the challenges of safe and efficient automatic berthing for underactuated inland ships without tugboat or lateral thruster assistance, this article introduces a phased predictive berthing control (PPBC) method designed for low-speed conditions with uncertainties. A maneuvering modeling group (MMG) model is initially developed, incorporating twin-propeller and twin-rudder configurations, environmental disturbances (i.e., wind and currents), and model uncertainties. Three distinct berthing strategies, i.e., bow-in berthing, parallel berthing, and stern-in berthing, are formulated to ensure the applicability for most of berthing scenarios with phased states constraints. A time-delay observer is designed to estimate environmental disturbances and model uncertainties, on the basis of which a reliable predictive model is constructed by using the low-speed MMG model and the estimated disturbances and uncertainties. Leveraging this model, a model predictive control (MPC) method is designed to achieve the trajectory tracking of berthing control, while accounting for both control input and phased-state constraints. Simulation results demonstrate that the proposed PPBC method outperforms conventional proportional–integral–derivative, sliding mode control, and standard MPC methods in terms of trajectory, heading, and speed tracking error across a range of evaluated berthing scenarios.
Keywords:
Automatic berthing
inland ships
low-speed maneuvering
phased berthing
trajectory and attitude tracking

Journal

IEEE Journal of Oceanic Engineering cover
IEEE Journal of Oceanic Engineering
IF:
5.3
Papers:
2.6K
Citations:
7.4K

Organization

W
wuhan university of technology
Scholars:
6.0K
Papers: 1.8K
Citations: 0
C
chalmers university of technology
Scholars:
1.5W
Papers: 1.6W
Citations: 10
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