Gaussian processes as port-Hamiltonian surrogate models make it possible to treat nonlinear Hamiltonian or effort functions in port-Hamiltonian differential equations, even and especially if they are not explicitly known. The project investigates how such surrogate models can be constructed from measured and synthetic data. A decisive advantage is that existing gaps in coupled port-Hamiltonian systems can be closed in a structure-preserving manner.
DFG Programme
Collaborative Research Centres
