Parametric model order reduction for large-scale and complex thermal systems

Daming Lou, Siep Weiland

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
5 Downloads (Pure)


In this paper, a parametric model order reduction (pMOR) technique is proposed to find a simplified system representation of a large-scale and complex thermal system. The main principle behind this technique is that any change of the physical parameters in the high-fidelity model can be updated directly in the simplified model. For deriving the parametric reduced model, a Krylov subspace method is employed which yields the relevant subspaces of the projected state. With the help of the projection operator, first moments of the low-rank model are set identical to the correspondent moments of the original model. Additionally, a prior upper bound of the error induced by the approximation is derived.
Original languageEnglish
Title of host publication2018 European Control Conference (ECC)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)978-3-9524-2698-2
Publication statusPublished - 27 Nov 2018
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus, Limassol, Cyprus
Duration: 12 Jun 201815 Jun 2018
Conference number: 16


Conference16th European Control Conference, ECC 2018
Abbreviated titleECC 2018


  • Model order reduction
  • Large-scale systems
  • Parametric model reduction


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