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Passivity preserving parametric model-order reduction for non-affine parameters

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  • Ortwin Farle
  • Stefan Burgard
  • Romanus Dyczij-Edlinger

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.

Suggested Citation

  • Ortwin Farle & Stefan Burgard & Romanus Dyczij-Edlinger, 2010. "Passivity preserving parametric model-order reduction for non-affine parameters," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 17(3), pages 279-294, December.
    • Handle: RePEc:taf:nmcmxx:v:17:y:2010:i:3:p:279-294
    DOI: 10.1080/13873954.2011.562901
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