A New Riemannian Framework for Efficient ℋ2-Optimal Model Reduction of Port-Hamiltonian Systems

We present a new framework for ℋ 2 -optimal model reduction of linear port-Hamiltonian systems. The approach retains structural properties of the original system, such as passivity, and is based on the efficient pole-residue formulation of the ℋ 2 -error norm. This makes Riemannian optimization computationally feasible for large-scale dynamical systems as well, which is supported by a numerical example.