Time-optimal control of ship manoeuvring under wave loads
Time-optimal control of ship manoeuvring under wave loads
Ship manoeuvrability of Maritime Autonomous Surface Ships (MASS) revolutionise the maritime industry. However, this paradigm shift necessitates the advancement of manoeuvring control models to meet the complex demands of autonomous navigation. This paper addresses the need for an improved manoeuvring control model for MASS, particularly concerning path planning and tracking in the presence of wave loads. The paper establishes a comprehensive mathematical model for ship manoeuvring, considering forces acting on the ship's hull, propellers, rudders, and wave loads. A time optimisation model using a spatial reformulation approach is introduced. A nonlinear Model Predictive Control (MPC) model is presented for path planning and tracking, with a case study investigating the influence of wave load and comparing two control strategies. 10%–20% of time consumption increases if the wave load exists. This research bridges the gap in existing literature by incorporating wave loads into MPC-based control models for MASS. The findings shed light on the significance of wave loads in ship manoeuvring and provide valuable insights into effective control strategies for autonomous vessels operating in real-world sea conditions.
model predictive control, path planning, time-optimal manoeuvring, trajectory tracking, wave loads, Model predictive control, Trajectory tracking, Time-optimal manoeuvring, Path planning, Wave load
Zhang, Ming
1f41798e-90f3-4a50-a681-da7c289fa862
Kim, Daejeong
2730cb06-0014-46d4-a4d0-1b27d65668b7
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Yuan, Zhi-Ming
21fc3d2c-1bfc-4d49-9ced-c335cb743baa
1 February 2024
Zhang, Ming
1f41798e-90f3-4a50-a681-da7c289fa862
Kim, Daejeong
2730cb06-0014-46d4-a4d0-1b27d65668b7
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Yuan, Zhi-Ming
21fc3d2c-1bfc-4d49-9ced-c335cb743baa
Zhang, Ming, Kim, Daejeong, Tezdogan, Tahsin and Yuan, Zhi-Ming
(2024)
Time-optimal control of ship manoeuvring under wave loads.
Ocean Engineering, 293, [116627].
(doi:10.1016/j.oceaneng.2023.116627).
Abstract
Ship manoeuvrability of Maritime Autonomous Surface Ships (MASS) revolutionise the maritime industry. However, this paradigm shift necessitates the advancement of manoeuvring control models to meet the complex demands of autonomous navigation. This paper addresses the need for an improved manoeuvring control model for MASS, particularly concerning path planning and tracking in the presence of wave loads. The paper establishes a comprehensive mathematical model for ship manoeuvring, considering forces acting on the ship's hull, propellers, rudders, and wave loads. A time optimisation model using a spatial reformulation approach is introduced. A nonlinear Model Predictive Control (MPC) model is presented for path planning and tracking, with a case study investigating the influence of wave load and comparing two control strategies. 10%–20% of time consumption increases if the wave load exists. This research bridges the gap in existing literature by incorporating wave loads into MPC-based control models for MASS. The findings shed light on the significance of wave loads in ship manoeuvring and provide valuable insights into effective control strategies for autonomous vessels operating in real-world sea conditions.
Text
OE-D-23-06913-revison clean version
- Accepted Manuscript
Restricted to Repository staff only until 5 January 2026.
Request a copy
Text
1-s2.0-S0029801823030111-main
- Version of Record
More information
Accepted/In Press date: 19 December 2023
e-pub ahead of print date: 5 January 2024
Published date: 1 February 2024
Additional Information:
Publisher Copyright:
© 2023 The Author(s)
Keywords:
model predictive control, path planning, time-optimal manoeuvring, trajectory tracking, wave loads, Model predictive control, Trajectory tracking, Time-optimal manoeuvring, Path planning, Wave load
Identifiers
Local EPrints ID: 485833
URI: http://eprints.soton.ac.uk/id/eprint/485833
ISSN: 0029-8018
PURE UUID: f034ff85-cf89-4552-9ea3-669dd83ef6c3
Catalogue record
Date deposited: 20 Dec 2023 17:33
Last modified: 18 Mar 2024 04:10
Export record
Altmetrics
Contributors
Author:
Ming Zhang
Author:
Daejeong Kim
Author:
Tahsin Tezdogan
Author:
Zhi-Ming Yuan
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics