Structure-Preserving Model Reduction Using a Krylov Subspace Projection Formulation

Abstract

A general framework for structure-preserving model reduction by Krylov subspace projection methods is developed. It not only matches as many moments as possible but also preserves substructures of importance in the coeficient matrices L,G,C, and B that define a dynamical system prescribed by the transfer function of the form H(s/) = L^*(G+sC)^-1B. Many existing structure-preserving model-order reduction methods for linear and second-order dynamical systems can be derived under this general framework. Furthermore, it also offers insights into the development of new structure-preserving model reduction methods.