Complexity reduction for uncertain systems: a projection-based approach

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This paper considers the problem of complexity reduction for systems with affine parametric uncertainty. We are interested in the relation between model reduction for a nominal plant and dimension reduction for a parameter vector. By using linear fractional representations of the system, it is shown that a projection-based reduction approach can be applied separately to the generalized plant and the uncertainty block. The error bounds between the original system and its reduced order approximation are derived, and a case study is used to validate our findings.

Originele taal-2Engels
Titel2016 IEEE 55th Conference on Decision and Control, CDC 2016
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Aantal pagina's6
ISBN van elektronische versie978-1-5090-1837-6
ISBN van geprinte versie978-1-5090-1838-3
StatusGepubliceerd - 27 dec 2016
Evenement55th IEEE Conference on Decision and Control (CDC 2016) - Aria Resort and Casino, Las Vegas, Verenigde Staten van Amerika
Duur: 12 dec 201614 dec 2016
Congresnummer: 55


Congres55th IEEE Conference on Decision and Control (CDC 2016)
Verkorte titelCDC02016
LandVerenigde Staten van Amerika
StadLas Vegas
Internet adres


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