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An adaptive flux observer for the permanent magnet synchronous motor
Author(s) -
Romero Jose Guadalupe,
Ortega Romeo,
Han Zhaoqiang,
Devos Thomas,
Malrait François
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2587
Subject(s) - control theory (sociology) , stator , observer (physics) , gradient descent , residual , permanent magnet synchronous motor , computer science , nonlinear system , convergence (economics) , synchronous motor , magnet , engineering , artificial intelligence , physics , algorithm , artificial neural network , mechanical engineering , control (management) , electrical engineering , quantum mechanics , economics , economic growth
Summary A gradient descent‐based nonlinear observer for surface‐mount permanent magnet synchronous motors with remarkable stability properties was recently proposed. A key assumption for the derivation of the observer is the knowledge of the electrical parameters, which are usually uncertain. In the present paper, we propose a robust adaptive flux observer adding immersion and invariance parameter adaptation algorithms to estimate the stator resistance. Global boundedness of all signals and convergence to a residual set of the flux estimation error is guaranteed. The performance of the new adaptive observer is assessed with realistic simulations. Copyright © 2015 John Wiley & Sons, Ltd.