A quasi-convex optimization approach to parameterized model order reduction

Authors:
Kin Cheong Sou;Alexandre Megretski;Luca Daniel
Affiliations:
Massachusetts Institute of Technology;Massachusetts Institute of Technology;Massachusetts Institute of Technology
Venue:
Proceedings of the 42nd annual Design Automation Conference
Year:
2005

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Abstract

In this paper an optimization based model order reduction (MOR) framework is proposed. The method involves setting up a quasiconvex program that explicitly minimizes a relaxation of the optimal H∞ norm MOR problem. The method generates guaranteed stable and passive reduced models and it is very flexible in imposing additional constraints. The proposed optimization approach is also extended to parameterized model reduction problem (PMOR). The proposed method is compared to existing moment matching and optimization based MOR methods in several examples. A PMOR model for a large RF inductor is also constructed.