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A Fuzzy Adaptative Backstepping Control Strategy for Marine Current Turbine under Disturbances and Uncertainties

Author

Listed:
  • Xusheng Shen

    (Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China)

  • Tao Xie

    (Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China)

  • Tianzhen Wang

    (Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China)

Abstract

Marine current energy is attracting more and more attention in the world as a reliable and highly predictable energy resource. However, conventional proportional integral (PI) control will be sensitive to the numerous challenges that exist in a marine current turbine system (MCTs) such as marine current disturbance, torque disturbance and other uncertain parameters. This paper proposes a fuzzy adaptive backstepping control (F-A-BC) approach for a marine current turbine system. The proposed F-A-BC strategy consisted of two parts. First, an adaptive backstepping control approach with the compensation of disturbance and uncertainty was designed to improve anti-interference of the MCT so that the maximum power point tracking (MPPT) was realized. Then, a fuzzy logic control approach was combined to adjust parameters of an adaptive backstepping control approach in real time. The effectiveness of the proposed controller was verified by the simulation of a direct-drive marine current turbine system. The simulation results showed that the F-A-BC has better anti-interference ability and faster convergence compared to the adaptive backstepping control, sliding mode control and fuzzy PI control strategies under disturbances. The error percentage of rotor speed could be reduced by 3.5% under swell effect compared to the conventional controller. Moreover, the robustness of the F-A-BC method under uncertainties was tested and analyzed. The simulation results also indicated that the proposed approach could slightly improve the power extraction capability of the MCTs under variable marine current speed.

Suggested Citation

  • Xusheng Shen & Tao Xie & Tianzhen Wang, 2020. "A Fuzzy Adaptative Backstepping Control Strategy for Marine Current Turbine under Disturbances and Uncertainties," Energies, MDPI, vol. 13(24), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6550-:d:460653
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    References listed on IDEAS

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    4. Johan Forslund & Anders Goude & Karin Thomas, 2018. "Validation of a Coupled Electrical and Hydrodynamic Simulation Model for a Vertical Axis Marine Current Energy Converter," Energies, MDPI, vol. 11(11), pages 1-13, November.
    5. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.
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    Cited by:

    1. Lu Liu & Yun Zeng, 2023. "Intelligent ISSA-Based Non-Singular Terminal Sliding-Mode Control of DC–DC Boost Converter Feeding a Constant Power Load System," Energies, MDPI, vol. 16(13), pages 1-23, June.
    2. Alimuddin Alimuddin & Ria Arafiyah & Irma Saraswati & Rocky Alfanz & Partogi Hasudungan & Taufik Taufik, 2021. "Development and Performance Study of Temperature and Humidity Regulator in Baby Incubator Using Fuzzy-PID Hybrid Controller," Energies, MDPI, vol. 14(20), pages 1-21, October.
    3. Btissam Majout & Houda El Alami & Hassna Salime & Nada Zine Laabidine & Youness El Mourabit & Saad Motahhir & Manale Bouderbala & Mohammed Karim & Badre Bossoufi, 2022. "A Review on Popular Control Applications in Wind Energy Conversion System Based on Permanent Magnet Generator PMSG," Energies, MDPI, vol. 15(17), pages 1-41, August.
    4. Sylvain S. Guillou & Eric Bibeau, 2023. "Tidal Turbines," Energies, MDPI, vol. 16(7), pages 1-5, April.

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