Effort- and flow-constraint reduction methods for structure preserving model reduction of port-Hamiltonian systems

Port-based network modeling of (lumped-parameter) physical systems leads directly to their representation as port-Hamiltonian systems which are an important class of passive state-space systems. At the same time modeling of physical systems often leads to high-dimensional dy namical models. State-space dimensions are enormously high as well if distributed-parameter models are spatially discretized. Therefore an important issue concerns model reduction of these high-dimensional systems, both for analysis and control. The goal of this work is to show that the specific model reduction techniques of linear portHamiltonian systems preserve port-Hamiltonian structure, and, as a consequence, passivity.