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Noncausal explicit model predictive control of wave energy converters

Gao, Teng; Zhang, Yao; Tezdogan, Tahsin; (2025) Noncausal explicit model predictive control of wave energy converters. Ocean Engineering , 338 , Article 121999. 10.1016/j.oceaneng.2025.121999. Green open access

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Abstract

Wave energy is a promising renewable energy source, but its commercial utilisation is low compared to wind and solar energy. This paper proposes an explicit model predictive control (EMPC) strategy to reduce the high computational burden associated with online computation. Realistic wave data collected from the coast of Cornwall, UK, together with realistic single-point absorber parameters, are utilised. The dynamic response of the floating system is controlled, and a disturbance observer and an autoregressive model are designed for wave prediction. This paper aims to identify the most effective strategy to achieve optimal trajectory tracking, rapid prediction, efficient optimisation, and maximum energy capture. The results of numerical simulations show impressive effects of trajectory tracking, wave prediction, and maximum energy capture, with rapid prediction and low computational demand. These results demonstrate the effectiveness of the proposed EMPC method in wave energy converters (WECs).

Type: Article
Title: Noncausal explicit model predictive control of wave energy converters
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.oceaneng.2025.121999
Publisher version: https://doi.org/10.1016/j.oceaneng.2025.121999
Language: English
Additional information: Copyright © 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Wave energy converters; Optimal control; Model predictive control; Robustness; Wave prediction
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10210874
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