On Improving TLS Identification Results Using Nuisance Variables with Application on PMSM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F21%3APU142091" target="_blank" >RIV/00216305:26620/21:PU142091 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9589402" target="_blank" >https://ieeexplore.ieee.org/document/9589402</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IECON48115.2021.9589402" target="_blank" >10.1109/IECON48115.2021.9589402</a>
Alternative languages
Result language
angličtina
Original language name
On Improving TLS Identification Results Using Nuisance Variables with Application on PMSM
Original language description
This article presents a novel total least-squares based method for errors-in-variables model identification 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 identified 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 identification 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/TN01000024" target="_blank" >TN01000024: National Competence Center - Cybernetics and Artificial Intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society
ISBN
978-1-6654-3554-3
ISSN
—
e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
neuveden
Event location
Toronto
Event date
Oct 13, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000767230601164