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dc.contributor.authorVan Vuuren, P.A.
dc.contributor.authorVan Schoor, G.
dc.date.accessioned2017-02-22T09:19:08Z
dc.date.available2017-02-22T09:19:08Z
dc.date.issued2011
dc.identifier.citationVan Vuuren, P.A. & Van Schoor, G. 2011. μ-Analysis applied to self-sensing active magnetic bearings. SAIEE Africa research journal, 102(4): 98-106. [https://www.saiee.org.za/DisplayCustomLink.aspx?name=2011:%20Vol%20102%20No%204]en_US
dc.identifier.issn1991-1696
dc.identifier.urihttp://hdl.handle.net/10394/20472
dc.identifier.urihttp://eolstoragewe.blob.core.windows.net/wm-418498-cmsimages/Publications/ARJ_documents/2011no4/102_4_2.pdf
dc.identifier.urihttp://www.saiee.org.za/DisplayCustomLink.aspx?name=2011:%20Vol%20102%20No%204
dc.description.abstractThe stability margin of a two degree-of-freedom self-sensing active magnetic bearing (AMB) is estimated by means of μ -analysis. The specific self-sensing algorithm implemented in this study is the direct current measurement method. Detailed black-box models are developed for the main subsystems in the AMB by means of discrete-time system identification. In order to obtain models for dynamic uncertainty in the various subsystems in the AMB, the identified models are combined to form a closed-loop model for the self-sensing AMB. The response of this closed-loop model is then compared to the original AMB’s response and models for the dynamic uncertainty are empirically deduced. Finally, the system’s stability margin for the modelled uncertainty is estimated by means of μ -analysis. The results show that μ -analysis is ill-equipped to estimate the stability margin of a nonlinear systemen_US
dc.language.isoenen_US
dc.publisherSAIEEEen_US
dc.subjectActive magnetic bearingsen_US
dc.subjectSystem identificationen_US
dc.subjectSelf-sensingen_US
dc.subjectμ -Analysisen_US
dc.titleμ-Analysis applied to self-sensing active magnetic bearingsen_US
dc.typeArticleen_US
dc.contributor.researchID10732926 - Van Vuuren, Pieter Andries
dc.contributor.researchID12134457 - Van Schoor, George


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