On Improving TLS Identication Results Using Nuisance Variables with Application on PMSM
dc.contributor.author | Friml, Dominik | cs |
dc.contributor.author | Kozubík, Michal | cs |
dc.contributor.author | Václavek, Pavel | cs |
dc.date.issued | 2021-11-13 | cs |
dc.description.abstract | This article presents a novel total least-squares based method for errors-in-variables model identication with a known structure. This method considers the errors of both input and output variables and thus achieves more accurate estimates compared to conventional ordinary least-squares based methods. The introduced method consists of two recursive total least-squares algorithms connected in a hierarchical structure, which allows for exploitation of nuisance variables and a priori known structure of the identied model. The total least-squares (TLS) method is introduced, and a new “nuisance improved hierarchical total least-squares” (nHTLS) method is derived. Its properties are discussed and proved by simulations. Furthermore, the method is applied in a practical experiment consisting of the state-space identication of the permanent magnet synchronous motor (PMSM). The introduced method is compared with TLS and proven to provide measurably superior dynamical behavior and smaller estimation error of results. | en |
dc.format | text | cs |
dc.format.extent | 1-6 | cs |
dc.format.mimetype | application/pdf | cs |
dc.identifier.citation | IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society. 2021, p. 1-6. | en |
dc.identifier.doi | 10.1109/IECON48115.2021.9589402 | cs |
dc.identifier.isbn | 978-1-6654-3554-3 | cs |
dc.identifier.orcid | 0000-0002-2013-6912 | cs |
dc.identifier.orcid | 0000-0002-6887-202X | cs |
dc.identifier.orcid | 0000-0001-8624-5874 | cs |
dc.identifier.other | 173146 | cs |
dc.identifier.researcherid | CRJ-4028-2022 | cs |
dc.identifier.researcherid | A-3448-2009 | cs |
dc.identifier.scopus | 57328576200 | cs |
dc.identifier.scopus | 8448897700 | cs |
dc.identifier.uri | http://hdl.handle.net/11012/202278 | |
dc.language.iso | en | cs |
dc.publisher | IEEE | cs |
dc.relation.ispartof | IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society | cs |
dc.relation.uri | https://ieeexplore.ieee.org/document/9589402 | cs |
dc.rights | (C) IEEE | cs |
dc.rights.access | openAccess | cs |
dc.subject | Total Least-Squares | en |
dc.subject | Errors-in-Variables | en |
dc.subject | Hierarchical Total Least-Squares | en |
dc.subject | Nuisance Variables | en |
dc.subject | PMSM Identication | en |
dc.title | On Improving TLS Identication Results Using Nuisance Variables with Application on PMSM | en |
dc.type.driver | conferenceObject | en |
dc.type.status | Peer-reviewed | en |
dc.type.version | acceptedVersion | en |
sync.item.dbid | VAV-173146 | en |
sync.item.dbtype | VAV | en |
sync.item.insts | 2025.02.03 15:39:30 | en |
sync.item.modts | 2025.01.17 16:52:04 | en |
thesis.grantor | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav automatizace a měřicí techniky | cs |
thesis.grantor | Vysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika a robotika | cs |
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