Nonlinear model predictive control for path following of autonomous inland vessels in confined waterways
Artikel i vetenskaplig tidskrift, 2025

Autonomous inland shipping offers a safer and more efficient form of transportation over water with the potential to reduce maritime carbon emissions. However, the operation of autonomous vessels presents unique challenges due to complex dynamics, varying traffic conditions, and environmental disturbances. To ensure the safe navigation of these vessels in confined inland waterways, it is crucial toaddress manoeuvring prediction and motion control challenges. Research focusing on these challenges disregards or only partially incorporates inland waterway characteristics related to the vessel and itssurroundings. This study provides a comprehensive analysis of these key factors. By modelling the vessel using a modified Manoeuvring Modelling Group (MMG) model specifically tailored for confinedwaterways, hydrodynamic effects due to shallow water, channel banks, and current are accounted for. A nonlinear model predictive controller (NMPC) is employed for the vessel path following control under various scenarios, including straight channels, confluences, and river bends. It is observed that the hydrodynamic effects from the channel banks significantly impact vessel steering. Compared toconventional proportional-integral-derivative (PID) controllers, NMPC effectively reduces course deviations and cross-track errors under varying water depth and ship-to-bank distance conditions, while alsorequiring fewer rudder deflections. Furthermore, key performance metrics related to the control of inland waterway vessels are proposed to evaluate the controller’s performance further. The NMPC control law demonstrates its effectiveness in capturing the hydrodynamic effects and improving navigation safety in confined waterways.

Författare

Chengqian Zhang

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Abhishek Dhyani

TU Delft

Jonas Ringsberg

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Fabian Thies

Chalmers, Mekanik och maritima vetenskaper, Marin teknik

Rudy R. Negenborn

TU Delft

Vasso Reppa

TU Delft

Ocean Engineering

0029-8018 (ISSN)

Vol. 334 1-19 121592

AUTOBarge - European training and research network on Autonomous Barges for Smart Inland Shipping

Europeiska kommissionen (EU) (EC/H2020/955768), 2021-10-01 -- 2025-09-30.

Styrkeområden

Informations- och kommunikationsteknik

Transport

Energi

Drivkrafter

Hållbar utveckling

Innovation och entreprenörskap

Ämneskategorier (SSIF 2025)

Transportteknik och logistik

Farkost och rymdteknik

Reglerteknik

Fundament

Grundläggande vetenskaper

DOI

10.1016/j.oceaneng.2025.121592

Mer information

Skapat

2025-06-13