Introduction to Krylov Subspace Methods in Model Order Reduction

In recent years, Krylov subspace methods have become popular tools for computing reduced order models of high order linear time invariant systems. The reduction can be done by applying a projection from high order to lower order space using the bases of some subspaces called input and output Krylov subspaces. The aim of this paper is to give an introduction into the principles of Krylov subspace based model reduction and to give a rough overview of the algorithms available for computation. A technical example illustrates the procedures.