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A Type-2 Fuzzy Controller for Floating Tension-Leg Platforms in Wind Turbines

Author

Listed:
  • Behnam Firouzi

    (Vibrations and Acoustics Laboratory (VAL), Mechanical Engineering Department, Ozyegin University, Istanbul 34794, Turkey)

  • Khalid A. Alattas

    (Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 21959, Saudi Arabia)

  • Mohsen Bakouri

    (Department of Medical Equipment Technology, College of Applied Medical Science, Majmaah University, Majmaah 11952, Saudi Arabia
    Department of Physics, College of Arts, Fezzan University, Traghen 71340, Libya)

  • Abdullah K. Alanazi

    (Department of Chemistry, Faculty of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Ardashir Mohammadzadeh

    (Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
    School of Engineering and Technology, Duy Tan University, Da Nang 550000, Vietnam)

  • Saleh Mobayen

    (Future Technology Research Center, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

  • Afef Fekih

    (Department of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA)

Abstract

This paper proposes a type-2 fuzzy controller for floating tension-leg platforms in wind turbines. Its main objective is to stabilize and control offshore floating wind turbines exposed to oscillating motions. The proposed approach assumes that the dynamics of all units are completely unknown. The latter are approximated using the proposed Sugeno-based type-2 fuzzy approach. A nonlinear Kalman-based algorithm is developed for parameter optimization, and linear matrix inequalities are derived to analyze the system’s stability. For the fuzzy system, both rules and membership functions are optimized. Additionally, in the designed approach, the estimation error of the type-2 fuzzy approach is also considered in the stability analysis. The effectiveness and performance of the proposed approach is assessed using a simulation study of a tension leg platform subject to various disturbance modes.

Suggested Citation

  • Behnam Firouzi & Khalid A. Alattas & Mohsen Bakouri & Abdullah K. Alanazi & Ardashir Mohammadzadeh & Saleh Mobayen & Afef Fekih, 2022. "A Type-2 Fuzzy Controller for Floating Tension-Leg Platforms in Wind Turbines," Energies, MDPI, vol. 15(5), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1705-:d:757979
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    References listed on IDEAS

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    2. Becky Corley & Sofia Koukoura & James Carroll & Alasdair McDonald, 2021. "Combination of Thermal Modelling and Machine Learning Approaches for Fault Detection in Wind Turbine Gearboxes," Energies, MDPI, vol. 14(5), pages 1-14, March.
    3. Piotr Derugo & Krzysztof Szabat & Tomasz Pajchrowski & Krzysztof Zawirski, 2022. "Fuzzy Adaptive Type II Controller for Two-Mass System," Energies, MDPI, vol. 15(2), pages 1-24, January.
    4. Zhang, Mingming & Li, Xin & Tong, Jingxin & Xu, Jianzhong, 2020. "Load control of floating wind turbine on a Tension-Leg-Platform subject to extreme wind condition," Renewable Energy, Elsevier, vol. 151(C), pages 993-1007.
    5. Piotr Gajewski & Krzysztof Pieńkowski, 2021. "Control of the Hybrid Renewable Energy System with Wind Turbine, Photovoltaic Panels and Battery Energy Storage," Energies, MDPI, vol. 14(6), pages 1-23, March.
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