Torque Ripple Suppression of Switched Reluctance Motor with Reference Torque Online Correction
نویسندگان
چکیده
High torque ripple dramatically affects the switched reluctance motor (SRM) application. To reduce ripple, a reference neural network (RTNN) is proposed to adjust online. Firstly, RTNN built on sharing function (TSF) method. Furthermore, designed as single-input and -output network. As periodic relationship between rotor angle, angle constitutes central node parameter of implicit in RTNN. Therefore, one-step adjustment can perform well at restraining torque. Lastly, error used parameters ripple. In MATLAB environment, through simulation comparison with fuzzy PD current compensation method, effectiveness suppression proven different loads speeds.
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ژورنال
عنوان ژورنال: Machines
سال: 2023
ISSN: ['2075-1702']
DOI: https://doi.org/10.3390/machines11020179