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Artículo
Influence of Covariance-Based ALS Methods in the Performance of Predictive Controllers With Rotor Current Estimation
dc.creator | Rodas, Jorge | es |
dc.creator | Martín Torres, Cristina | es |
dc.creator | Arahal, Manuel R. | es |
dc.creator | Barrero, Federico | es |
dc.creator | Gregor, Raúl | es |
dc.date.accessioned | 2024-09-27T12:53:24Z | |
dc.date.available | 2024-09-27T12:53:24Z | |
dc.date.issued | 2017-04 | |
dc.identifier.citation | Rodas, J., Martín, C., Arahal, M.R., Barrero, F. y Gregor, R. (2017). Influence of Covariance-Based ALS Methods in the Performance of Predictive Controllers With Rotor Current Estimation. IEEE Transactions on Industrial Electronics, 64 (4), 2602-2607. https://doi.org/10.1109/TIE.2016.2636205. | |
dc.identifier.issn | 0278-0046 | es |
dc.identifier.uri | https://hdl.handle.net/11441/163011 | |
dc.description.abstract | The use of online rotor current estimators with predictive current controllers has been very recently stated in five-phase induction motor drives, where the closed-loop performance of the system is improved by using suboptimal estimators based on Kalman filters. In this paper, the interest of using optimization methods in the definition of the Kalman filter, like the covariance technique, is analyzed. Obtained system performances using optimal and suboptimal rotor current estimators are experimentally compared. | es |
dc.format | application/pdf | es |
dc.format.extent | 6 p. | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. (IEEE) | es |
dc.relation.ispartof | IEEE Transactions on Industrial Electronics, 64 (4), 2602-2607. | |
dc.subject | Rotors | es |
dc.subject | Estimation | es |
dc.subject | Stators | es |
dc.subject | Current measurement | es |
dc.subject | Predictive models | es |
dc.subject | Tuning | es |
dc.subject | Kalman filters | es |
dc.title | Influence of Covariance-Based ALS Methods in the Performance of Predictive Controllers With Rotor Current Estimation | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería Eléctrica | es |
dc.relation.projectID | DPI2013-44278-R | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/7775089 | es |
dc.identifier.doi | 10.1109/TIE.2016.2636205 | es |
dc.contributor.group | Universidad de Sevilla. TEP196: Sistemas de Energía Eléctrica | es |
dc.journaltitle | IEEE Transactions on Industrial Electronics | es |
dc.publication.volumen | 64 | es |
dc.publication.issue | 4 | es |
dc.publication.initialPage | 2602 | es |
dc.publication.endPage | 2607 | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | es |
dc.contributor.funder | Universidad de Sevilla | es |
Ficheros | Tamaño | Formato | Ver | Descripción |
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IEEETIE_2017_Rodas_Martin_Infl ... | 7.216Mb | [PDF] | Ver/ | Versión aceptada |
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