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 coecient matrices L;G;C, and B that dene 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 oers insights into the development of new structure-preserving model reduction methods.