Passive reduced-order modeling via Krylov-subspace methods

Abstract

Krylov-subspace methods have become popular tools for reduced-order modeling of large-scale time-invariant linear dynamical systems. These techniques produce in a Pade sense optimal reduced-order models. However, when applied to passive systems, the Pade models do not preserve passivity in general. We describe a Krylov-subspace technique that generates passive reduced-order models. Results of numerical experiments with a passive system arising in VLSI circuit simulation are reported.