State and Force Observers Based on Multibody Models and the Indirect Kalman Filter

UDC.coleccionInvestigaciónes_ES
UDC.departamentoEnxeñaría Naval e Industriales_ES
UDC.endPage228es_ES
UDC.grupoInvLaboratorio de Enxeñaría Mecánica (LIM)es_ES
UDC.journalTitleMechanical Systems and Signal Processinges_ES
UDC.startPage210es_ES
UDC.volume106es_ES
dc.contributor.authorSanjurjo, Emilio
dc.contributor.authorDopico, Daniel
dc.contributor.authorLuaces, Alberto
dc.contributor.authorNaya, Miguel A.
dc.date.accessioned2025-02-20T08:40:49Z
dc.date.available2025-02-20T08:40:49Z
dc.date.issued2018-06
dc.descriptionAccepted manuscriptes_ES
dc.description.abstract[Abstract] The aim of this work is to present two new methods to provide state observers by combining multibody simulations with indirect extended Kalman filters. One of the methods presented provides also input force estimation. The observers have been applied to two mechanism with four different sensor configurations, and compared to other multibody-based observers found in the literature to evaluate their behavior, namely, the unscented Kalman filter (UKF), and the indirect extended Kalman filter with simplified Jacobians (errorEKF). The new methods have some more computational cost than the errorEKF, but still much less than the UKF. Regarding their accuracy, both are better than the errorEKF. The method with input force estimation outperforms also the UKF, while the method without force estimation achieves results almost identical to those of the UKF. All the methods have been implemented as a reusable MATLAB® toolkit which has been released as Open Source in https://github.com/MBDS/mbde-matlab.es_ES
dc.description.sponsorshipThis work has been partially financed by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU-ERDF funds under the projects ‘Observadores de estados y entradas basados en modelos multicuerpo detallados aplicados al control de vehículos’ (TRA2014-59435-P) and ‘Diseño y control óptimo eficiente de sistemas multicuerpo basado en técnicas de análisis de sensibilidad’ (DPI2016-81005-P), and by the Galician Government through grant ED431B2016/031.es_ES
dc.description.sponsorshipXunta de Galicia; ED431B2016/031es_ES
dc.identifier.citationE. Sanjurjo, D. Dopico, A. Luaces, M.Á. Naya, State and force observers based on multibody models and the indirect Kalman filter, Mechanical Systems and Signal Processing 106 (2018) 210–228. https://doi.org/10.1016/j.ymssp.2017.12.041es_ES
dc.identifier.doihttps://doi.org/10.1016/j.ymssp.2017.12.041
dc.identifier.issn1096-1216
dc.identifier.urihttp://hdl.handle.net/2183/41220
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TRA2014-59435-P/ES/OBSERVADORES DE ESTADOS Y ENTRADAS BASADOS EN MODELOS MULTICUERPO DETALLADOS APLICADOS AL CONTROL DE VEHICULOSes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/DPI2016-81005-P/ES/DISEÑO Y CONTROL ÓPTIMO EFICIENTE DE SISTEMAS MULTICUERPO BASADO EN TÉCNICAS DE ANÁLISIS DE SENSIBILIDADes_ES
dc.relation.urihttps://doi.org/10.1016/j.ymssp.2017.12.041es_ES
dc.rightsCC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectMultibody dynamicses_ES
dc.subjectKalman filteres_ES
dc.subjectState observeres_ES
dc.subjectForce estimationes_ES
dc.titleState and Force Observers Based on Multibody Models and the Indirect Kalman Filteres_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
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relation.isAuthorOfPublicationc20ab7a3-b7bb-49b1-a8e8-d215f3213698
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relation.isAuthorOfPublicationa09ae53f-86a3-4593-8b40-a29e2cea2ec4
relation.isAuthorOfPublication.latestForDiscovery85cc925c-e474-4427-bc4e-15d537b2ab75

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