Passivity preserving parametric model-order reduction for non-affine parameters
Ortwin Farle,
Stefan Burgard and
Romanus Dyczij-Edlinger
Mathematical and Computer Modelling of Dynamical Systems, 2010, vol. 17, issue 3, 279-294
Abstract:
Parametric model-order reduction (pMOR) has become a well-established technology for analysing large-scale systems with multiple parameters. However, the treatment of non-affine parameters is still posing significant challenges, because projection-based order-reduction methods cannot be applied directly. A common remedy is to establish affine parameter-dependencies approximately, but present extraction methods do not take important system properties, such as passivity, into account. This article proposes a new order-reduction approach that preserves passivity, reciprocity and causality and applies to a wide class of linear time-invariant (LTI) systems. We present the theory of the suggested method and demonstrate its practical usefulness by numerical examples taken from computational electromagnetics.
Date: 2010
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2011.562901 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:17:y:2010:i:3:p:279-294
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20
DOI: 10.1080/13873954.2011.562901
Access Statistics for this article
Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch
More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().