Block Krylov subspace methods for large-scale matrix computations in control

In this paper we show how to improve the approximate solution of the large Sylvester equation obtained by an arbitrary method. Such problems appear in many areas of control theory such as the computation of Hankel singular values, model reduction algorithms and others. Moreover, we propose a new method based on refinement process and weighted block Arnoldi algorithm for solving large Sylvester matrix equation. The numerical tests report the effectiveness of these methods.