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Global adaptive linear control of the permanent‐magnet synchronous motor
Author(s) -
Loria Antonio,
EspinosaPérez Gerardo,
AvilaBecerril Sofía
Publication year - 2014
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.2421
Subject(s) - control theory (sociology) , parametric statistics , controller (irrigation) , stator , rotor (electric) , adaptive control , convergence (economics) , exponential stability , torque , stability (learning theory) , synchronous motor , computer science , mathematics , nonlinear system , engineering , control (management) , physics , electrical engineering , artificial intelligence , mechanical engineering , statistics , quantum mechanics , machine learning , economic growth , agronomy , economics , biology , thermodynamics
SUMMARY We contribute with a linear time‐varying controller for the permanent magnet synchronous motor. We solve the open problem of speed‐tracking control by measuring only stator currents and the rotor angular positions, under parametric uncertainty. Integral action is used to compensate for the effects of the unknown load‐torque, and adaptation is employed to estimate the unknown parameters. In the case that parameters are known (except for the load), we show that the origin of the closed‐loop system is uniformly globally exponentially stable. For the case of unknown parameters, we prove uniform global asymptotic stability; hence, we establish parametric convergence. In contrast to other adaptive control schemes for electrical machines, we use a reduced‐order adaptive controller. Indeed, adaptation is used only for the electrical dynamics equations. Moreover, not surprisingly, the closed‐loop system has a structure well‐studied in adaptive‐control literature. Performance is illustrated in a numerical setting. Copyright © 2013 John Wiley & Sons, Ltd.