Adaptive super-twisting control of doubly salient permanent magnet generator for tidal stream turbine

Abstract Tidal Stream Turbine (TST) becomes more and more important due to the serious environmental and energy issues. Doubly Salient Permanent Magnet Generator (DSPMG), a fascinating machine with durable design, large torque, and high-power density, has a great prospect in TST. Nevertheless, the flux linkage and inductance of this machine have the same periodical variation due to the stator-Permanent Magnet (PM) structure. It not only causes the inherent torque ripple with the conventional sinusoidal current waveform but also makes the system nonlinear and strongly coupled even after the coordinate transformation. Thus, in order to control the complex systems stably and accurately, High-Order Sliding Mode Control (HOSMC) strategy based on Adaptive Super-Twisting Algorithm (ASTA) is proposed for DSPMG-based TST in this paper. Firstly, First-Order Sliding Mode Control (FOSMC) and Super-Twisting Algorithm (STA)-based HOSMC are designed respectively for the current loop in d-q coordinate system. Then, considering the difficulties of the parameters tuning timely in variable conditions, adaptive control is applied to STA-based HOSMC. The stability of this system in a finite time is proved subsequently. Eventually, according to the simulation results, ASTA-based HOSMC has the least torque ripple, highest control accuracy, and strongest robustness compared with the other controllers.

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