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 hal.structure.identifier
OUESLATI, Marouene
178374 Laboratoire des Sciences de l'Information et des Systèmes : Ingénierie Numérique des Systèmes Mécaniques [LSIS- INSM]
104752 Inria Lille - Nord Europe
dc.contributor.author
 hal.structure.identifier
THIERY, Stéphane
104752 Inria Lille - Nord Europe
178374 Laboratoire des Sciences de l'Information et des Systèmes : Ingénierie Numérique des Systèmes Mécaniques [LSIS- INSM]
dc.contributor.author
 hal.structure.identifier
GIBARU, Olivier
178374 Laboratoire des Sciences de l'Information et des Systèmes : Ingénierie Numérique des Systèmes Mécaniques [LSIS- INSM]
104752 Inria Lille - Nord Europe
dc.contributor.author
 hal.structure.identifier
BEAREE, Richard
178374 Laboratoire des Sciences de l'Information et des Systèmes : Ingénierie Numérique des Systèmes Mécaniques [LSIS- INSM]
dc.contributor.author
 hal.structure.identifier
MORARU, George
178374 Laboratoire des Sciences de l'Information et des Systèmes : Ingénierie Numérique des Systèmes Mécaniques [LSIS- INSM]
dc.date.accessioned2015
dc.date.available2015
dc.date.issued2011
dc.date.submitted2015
dc.identifier.isbn978-88-903724-7-6
dc.identifier.urihttp://hdl.handle.net/10985/10131
dc.description.abstractThis article address the identification problem of the natural frequency and the damping ratio of a second order continuous system where the input is a sinusoidal signal. An algebra based approach for identifying parameters of a Mass Spring Damper (MSD) system is proposed and compared to the Kalman-Bucy filter. The proposed estimator uses the algebraic parametric method in the frequency domain yielding exact formula, when placed in the time domain to identify the unknown parameters. We focus on finding the optimal sinusoidal exciting trajectory which allow to minimize the variance of the identification algorithms. We show that the variance of the estimators issued from the algebraic identification method introduced by Fliess and Sira-Ramirez is less sensitive to the input frequency than the ones obtained by the classical recursive Kalman-Bucy filter. Unlike conventional estimation approach, where the knowledge of the statistical properties of the noise is required, algebraic method is deterministic and non-asymptotic. We show that we don't need to know the variance of the noise so as to perform these algebraic estimators. Moreover, as they are non-asymptotic, we give numerical results where we show that they can be used directly for online estimations without any special setting.
dc.language.isoen
dc.publisherIMAACA
dc.rightsPost-print
dc.subjectParameter estimation; Recursive algorithm; Kalman-Bucy algorithm; Forgetting factor; Algebraic approach; Laplace transform; Operational calculus; Leibniz formula; Integral rules; Filtering
dc.titleOn Algebraic Approach for MSD Parametric Estimation
dc.typdocCommunication avec acte
dc.localisationCentre de Aix en Provence
dc.localisationCentre de Lille
dc.subject.halSciences de l'ingénieur: Automatique / Robotique
ensam.audienceInternationale
ensam.conference.title5th International Conference on Integrated Modeling and Analysis in Applied Control and Automation conference, IMAACA 2011
ensam.conference.date2011-09-12
ensam.countryItalie
ensam.title.proceeding5th International Conference on Integrated Modeling and Analysis in Applied Control and Automation conference, IMAACA 2011
ensam.page83-91
ensam.cityRome
hal.identifierhal-01203529
hal.version1
hal.submission.permittedupdateMetadata
hal.statusaccept


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