In this paper, a new structure-preserving method for the reduction of linear port-Hamiltonian systems with dissipation using Krylov subspaces is presented. It is shown how to choose the projection matrices in order to guarantee the moment matching property and to obtain a passive and thus stable reduced order model in port-Hamiltonian form. The method is suitable for the reduction of large-scale systems as it employs the well-known Arnoldi algorithm and matrix-vector multiplications to compute the reduced-order model.      «

In this paper, a new structure-preserving method for the reduction of linear port-Hamiltonian systems with dissipation using Krylov subspaces is presented. It is shown how to choose the projection matrices in order to guarantee the moment matching property and to obtain a passive and thus stable reduced order model in port-Hamiltonian form. The method is suitable for the reduction of large-scale systems as it employs the well-known Arnoldi algorithm and matrix-vector multiplications to compute t...     »