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

Yu-Chen Lin, Valentina Balas, Ji-Fan Yang and Yu-Heng Chang
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Yu-Chen Lin: Department of Automatic Control Engineering, Feng Chia University, Taichung 40724, Taiwan
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

Energies, 2020, vol. 13, issue 20, 1-18

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.

Keywords: model predictive torque control; adaptive Takagi-Sugeno (T–S) fuzzy model; permanent magnet synchronous generator (PMSG); hydrokinetic turbine systems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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