McCullough, D.R., Jones, B., Villarreal, O.J.G. et al. (1 more author) (2021) Towards control of autonomous surface vehicles in rough seas. In: Findeisen, R., Hirche, S., Janschek, K. and Mönnigmann, M., (eds.) IFAC-PapersOnLine. 21st IFAC World Congress 2020, 11-17 Jul 2020, Berlin, Germany. International Federation of Automatic Control (IFAC) , pp. 14692-14697.
Abstract
This paper addresses the problem of controlling an Autonomous Surface Vehicle (ASV) in rough sea-states, with a view towards minimising wave-induced forces, whilst maintaining headway. This is a challenging control application since, and as is derived in the paper, the interaction between the vessel and the wave disturbance is nonlinear and coupled. This subsequently motivates the novel application of the Real Time Iteration Scheme (RTI) for Nonlinear Model Predictive Control (NMPC) of the ASV. Analysis of the resulting control signal provides an important insight into the role of the wave encounter frequency. Specifically, by actuating at twice the average wave encounter frequency, the nonlinear controller is able to reduce the wave forces, compared to an open-loop controller that achieves the same average velocity.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0). |
Keywords: | Nonlinear; optimal marine system control; autonomous surface vehicle; nonlinear model predictive control; real time optimization |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Mar 2020 11:28 |
Last Modified: | 11 May 2021 10:27 |
Status: | Published |
Publisher: | International Federation of Automatic Control (IFAC) |
Refereed: | Yes |
Identification Number: | 10.1016/j.ifacol.2020.12.1832 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157784 |