Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2015-03, Vol.26 (3), p.640-645
Hauptverfasser:	Yu, Jinpeng, Shi, Peng, Dong, Wenjie, Chen, Bing, Lin, Chong
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive control systems Adaptive systems Approximation methods Artificial neural networks Backstepping Complexity theory Computer simulation Differential scanning calorimetry Dynamical systems dynamics surface control (DSC) Explosions Learning systems Magnetics - methods Magnetics - trends Neural networks Neural Networks (Computer) neural networks (NNs) Nonlinear dynamics nonlinear system permanent magnet synchronous motor (PMSM) Permanent magnets Synchronous motors Systems Analysis
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