Open AccessNeuro-Fuzzy Control of Interior Permanent Magnet Synchronous Motors: Stability Analysis and Implementation
Author(s) -
Dong Quang Dang,
Nga ThiThuy Vu,
Han Ho Choi,
JinWoo Jung
Publication year - 2013
Publication title -
journal of electrical engineering and technology/journal of electrical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.226
H-Index - 27
eISSN - 2093-7423
pISSN - 1975-0102
DOI - 10.5370/jeet.2013.8.6.1439
Subject(s) - permanent magnet synchronous motor , control theory (sociology) , magnet , control (management) , control engineering , fuzzy logic , stability (learning theory) , computer science , engineering , mechanical engineering , artificial intelligence , machine learning
-Thispaperinvestigatesarobustneurofuzzycontrol(NFC)methodwhichcanaccurately followthespeedreferenceofaninteriorpermanentmagnetsynchronousmotor(IPMSM)inthe existenceofnonlinearitiesandsystemuncertainties.Aneurofuzzycontroltermisproposedto estimatethesenonlinearanduncertainfactors,therefore,thisdifficultyiscompletelysolved.Tomake theglobalstabilityanalysissimpleandsystematic,thetimederivativeofthequadraticLyapunov functionisselectedasthecostfunctiontobeminimized.Moreover,thedesignprocedureoftheonline selftuningalgorithmiscomparativelysimplifiedtoreduceacomputationalburdenoftheNFC.Next, arotorangularaccelerationisobtainedthroughthedisturbanceobserver.Theproposedobserverbased NFCstrategycanachievebettercontrolperformance(i.e.,lesssteadystateerror,lesssensitivity)than thefeedbacklinearizationcontrolmethodevenwhenthereexistsomeuncertaintiesintheelectrical andmechanicalparameters.Finally,thevalidityoftheproposedneurofuzzyspeedcontrolleris confirmedthroughsimulationandexperimentalstudiesonaprototypeIPMSMdrivesystemwitha TMS320F28335DSP.