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Research Article | Open Access

A safe-by-design approach based on safe Bayesian optimization for tuning individual pitch controllers on floating offshore wind turbines

Aolong Fu1Yanhua Liu1,2( )Jianglin Lan3Ziyang Han1Shuo Shi4Zhenbin Zhang1
School of Electrical Engineering, Shandong University, Jinan 250061, China
Shenzhen Research Institute of Shandong University, A301, Virtual University Park in South District of Shenzhen, Shenzhen 200900, China
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
State Grid Shandong Electric Power Research Institute, Jinan 250000, China
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Abstract

Individual pitch control (IPC) effectively mitigates the structural loads on floating offshore wind turbines (FOWTs). However, conventional optimization methods for IPC tuning can explore unsafe parameters. To alleviate this critical safety risk, this paper proposes a safe-by-design framework based on safe Bayesian optimization (SafeBO) for automated tuning of a proportional-integral-based individual pitch controller. Unlike standard optimization methods, the framework restricts the search to regions remaining above a predefined safety threshold, guaranteeing zero safety violations across all tested scenarios and defined metrics. The final SafeBO-tuned controller demonstrates exceptional performance. Under challenging sea states, it reduces the platform pitch motion and tower fatigue loads by 20.3% and 12.8%, respectively, from those of conventionally tuned baseline controllers, without compromising the power production. These findings confirm that the SafeBO framework effectively resolves the safety–performance tradeoff, offering a robust and practical solution for safe, autonomous optimization of FOWT control systems.

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Article number: 9470012

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Cite this article:
Fu A, Liu Y, Lan J, et al. A safe-by-design approach based on safe Bayesian optimization for tuning individual pitch controllers on floating offshore wind turbines. Ocean, 2025, 1(1): 9470012. https://doi.org/10.26599/OCEAN.2025.9470012

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Received: 21 July 2025
Revised: 25 October 2025
Accepted: 30 October 2025
Published: 16 January 2026
© The author(s) 2025. Published by Tsinghua University Press.

This article is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the original author(s) and the source, a link to the license is provided, and any changes made are indicated. See http://creativecommons.org/licenses/by/4.0/