Finite-Time Stabilization of Floating Offshore Wind Turbines Under Wind and Wave Disturbances by Adaptive Barrier-Function Fractional-Order Sliding Mode Control

Floating offshore wind turbines harness more vigorous and more stable winds, making them a promising solution for clean energy. However, their stability is compromised by sea waves and sudden winds, reducing power extraction. To address these challenges, this paper proposes a finite-time fractional-order adaptive sliding mode controller for tension-leg platform wind turbines to enhance stability and efficiency. A fractional-order model ensures accurate system representation, while a barrier-function-based adaptive control strategy guarantees rapid, finite-time convergence, mitigates chattering, and suppresses external disturbances through real-time estimation. The proposed controller effectively stabilizes the system, helping to maximize power extraction. Simulation results in the MATLAB-Simulink environment demonstrate superior performance compared to conventional methods in terms of disturbance rejection and convergence speed. Furthermore, hardware-in-the-loop validation using a Speedgoat platform confirms the method's real-time feasibility and robustness under realistic operational conditions. The proposed approach offers a significant advancement in floating offshore wind turbines stability and control, ensuring efficient energy harvesting even under severe environmental disturbances. These findings contribute to the development of more reliable and resilient floating wind energy systems, supporting the transition toward sustainable offshore wind power.

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Publication Details

Journal
IEEE Transactions on Sustainable Energy
Published
2025-04-21
DOI
https://doi.org/10.1109/tste.2025.3563086
Citations
6
Primary Topic
Wave and Wind Energy Systems
Type
article
Field-Weighted Citation Impact
6.87
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article

Finite-Time Stabilization of Floating Offshore Wind Turbines Under Wind and Wave Disturbances by Adaptive Barrier-Function Fractional-Order Sliding Mode Control

Abolfazl Jalilvand, Mohammadreza Askari Sepestanaki, Seyed Hossein Rouhani, Saleh Mobayen et al.
6 citations
IEEE Transactions on Sustainable Energy
Wave and Wind Energy Systems
6.87
article

Finite-Time Stabilization of Floating Offshore Wind Turbines Under Wind and Wave Disturbances by Adaptive Barrier-Function Fractional-Order Sliding Mode Control

Abolfazl Jalilvand, Mohammadreza Askari Sepestanaki, Seyed Hossein Rouhani, Saleh Mobayen, Matin Jozeslami, Maedeh Nafisifar
article en
6 citations

Abstract

Floating offshore wind turbines harness more vigorous and more stable winds, making them a promising solution for clean energy. However, their stability is compromised by sea waves and sudden winds, reducing power extraction. To address these challenges, this paper proposes a finite-time fractional-order adaptive sliding mode controller for tension-leg platform wind turbines to enhance stability and efficiency. A fractional-order model ensures accurate system representation, while a barrier-function-based adaptive control strategy guarantees rapid, finite-time convergence, mitigates chattering, and suppresses external disturbances through real-time estimation. The proposed controller effectively stabilizes the system, helping to maximize power extraction. Simulation results in the MATLAB-Simulink environment demonstrate superior performance compared to conventional methods in terms of disturbance rejection and convergence speed. Furthermore, hardware-in-the-loop validation using a Speedgoat platform confirms the method's real-time feasibility and robustness under realistic operational conditions. The proposed approach offers a significant advancement in floating offshore wind turbines stability and control, ensuring efficient energy harvesting even under severe environmental disturbances. These findings contribute to the development of more reliable and resilient floating wind energy systems, supporting the transition toward sustainable offshore wind power.

IEEE Transactions on Sustainable EnergyVol. 16(4)
National Kaohsiung University of Science and Technology (TW), National Yunlin University of Science and Technology (TW), University of Zanjan (IR)
Affordable and clean energy
Openalex Percentile: Top 3%
Wave and Wind Energy Systems
6.87
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