TY - GEN
T1 - A New Riemannian Framework for Efficient H2-Optimal Model Reduction of Port-Hamiltonian Systems
AU - Moser, Tim
AU - Lohmann, Boris
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/14
Y1 - 2020/12/14
N2 - We present a new framework for H2-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 H2-error norm. This makes Riemannian optimization computationally feasible for large-scale dynamical systems as well, which is supported by a numerical example.
AB - We present a new framework for H2-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 H2-error norm. This makes Riemannian optimization computationally feasible for large-scale dynamical systems as well, which is supported by a numerical example.
UR - http://www.scopus.com/inward/record.url?scp=85099883197&partnerID=8YFLogxK
U2 - 10.1109/CDC42340.2020.9304134
DO - 10.1109/CDC42340.2020.9304134
M3 - Conference contribution
AN - SCOPUS:85099883197
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5043
EP - 5049
BT - 2020 59th IEEE Conference on Decision and Control, CDC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 59th IEEE Conference on Decision and Control, CDC 2020
Y2 - 14 December 2020 through 18 December 2020
ER -