Adaptive composite learning dynamic surface control for chaotic fractional-order permanent magnet synchronous motors

نویسندگان

چکیده

This paper aims to address the tracking problem of uncertain fractional-order permanent magnet synchronous motors with parametric uncertainties. To guarantee system stability and offset effect uncertainties, an adaptive backstepping composite learning neural control scheme based on interval excitation is presented. Moreover, dynamic surface technique exploited overcome technical limitation “explosion complexity” caused by standard framework. In virtue analysis illustrative simulation, it confirmed that proposed not only attenuates error as small possible, but also achieves satisfactory convergence high estimation precision.

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ژورنال

عنوان ژورنال: Frontiers in Applied Mathematics and Statistics

سال: 2022

ISSN: ['2297-4687']

DOI: https://doi.org/10.3389/fams.2022.1059756