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Adaptive Takagi–Sugeno Fuzzy Model Predictive Control for Permanent Magnet Synchronous Generator-Based Hydrokinetic Turbine Systems

Author

Listed:
  • Yu-Chen Lin

    (Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan)

  • Valentina Emilia Balas

    (Automatics and Applied Software Department, Aurel Vlaicu University of Arad, 310130 Arad, Romania)

  • Ji-Fan Yang

    (Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan)

  • Yu-Heng Chang

    (Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan)

Abstract

This paper presents a sensorless model predictive torque control strategy based on an adaptive Takagi–Sugeno (T–S) fuzzy model for the design of a six–phase permanent magnet synchronous generator (PMSG)–based hydrokinetic turbine systems (PMSG-HTs), which not only provides clean electric energy and stable energy-conversion efficiency, but also improves the reliability and robustness of the electricity supply. An adaptive T–S fuzzy model is first formed to characterize the nonlinear system of the PMSG before a model predictive torque controller based on the T–S fuzzy model for the PMSG system is employed to indirectly control the stator current and the stator flux magnitude, which improves the performance in terms of anti–disturbance, and achieves maximum hydropower tracking. Finally, we consider two types of tidal current, namely the mixed semidiurnal tidal current and the northwest European shelf tidal current. The simulation results demonstrate that the proposed control strategy can significantly improve the voltage–support capacity, while ensuring the stable operation of the PMSG in hydrokinetic turbine systems, especially under uneven tidal current speed conditions.

Suggested Citation

  • Yu-Chen Lin & Valentina Emilia Balas & Ji-Fan Yang & Yu-Heng Chang, 2020. "Adaptive Takagi–Sugeno Fuzzy Model Predictive Control for Permanent Magnet Synchronous Generator-Based Hydrokinetic Turbine Systems," Energies, MDPI, vol. 13(20), pages 1-18, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5296-:d:426604
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    References listed on IDEAS

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    1. Yun-Su Kim & Il-Yop Chung & Seung-Il Moon, 2015. "Tuning of the PI Controller Parameters of a PMSG Wind Turbine to Improve Control Performance under Various Wind Speeds," Energies, MDPI, vol. 8(2), pages 1-20, February.
    2. Faruk Guner & Hilmi Zenk, 2020. "Experimental, Numerical and Application Analysis of Hydrokinetic Turbine Performance with Fixed Rotating Blades," Energies, MDPI, vol. 13(3), pages 1-15, February.
    3. Ahmed Nasr & Chunyang Gu & Serhiy Bozhko & Chris Gerada, 2020. "Performance Enhancement of Direct Torque-Controlled Permanent Magnet Synchronous Motor with a Flexible Switching Table," Energies, MDPI, vol. 13(8), pages 1-15, April.
    4. Robins, Peter E. & Neill, Simon P. & Lewis, Matt J. & Ward, Sophie L., 2015. "Characterising the spatial and temporal variability of the tidal-stream energy resource over the northwest European shelf seas," Applied Energy, Elsevier, vol. 147(C), pages 510-522.
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