Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems
arXiv:2604.13297v1 Announce Type: cross
Abstract: This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and stability properties. We propose a novel neural-networ…