Order and structural dependence selection of LPV-ARX models using a nonnegative Garrote approach

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

24 Citaten (Scopus)
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Samenvatting

In order to accurately identify linear parameter-varying (LPV) systems, order selection of LPV linear regression models has prime importance. Existing identification approaches in this context suffer from the drawback that a set of functional dependencies needs to be chosen a priori for the parametrization of the model coefficients. However in a black-box setting, it has not been possible so far to decide which functions from a given set are required for the parametrization and which are not. To provide a practical solution, a nonnegative garrote approach is applied. It is shown that using only a measured data record of the plant, both the order selection and the selection of structural coefficient dependence can be solved by the proposed method.
Originele taal-2Engels
TitelProceedings of the 48th IEEE Conference on Decision and Control (CDC 2009), 16-18 December 2009, Shanghai, China
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's7406-7411
ISBN van geprinte versie978-1-4244-3871-6
DOI's
StatusGepubliceerd - 2009
Evenement48th IEEE Conference on Decision and Control (CDC 2009) - "Shanghai International Convention Center", Shanghai, China
Duur: 16 dec 200918 dec 2009
Congresnummer: 48
http://people.bu.edu/johnb/CDC2009-cfp.pdf

Congres

Congres48th IEEE Conference on Decision and Control (CDC 2009)
Verkorte titelCDC 2009
LandChina
StadShanghai
Periode16/12/0918/12/09
Ander48th IEEE Conference on Decision and Control, 2009
Internet adres

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