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

Tim Moser; Boris Lohmann

doi:10.1109/CDC42340.2020.9304134

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

Tim Moser
, Boris Lohmann

Chair of Automatic Control

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2020 59th IEEE Conference on Decision and Control, CDC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5043-5049
Number of pages	7
ISBN (Electronic)	9781728174471
DOIs	https://doi.org/10.1109/CDC42340.2020.9304134
State	Published - 14 Dec 2020
Event	59th IEEE Conference on Decision and Control, CDC 2020 - Virtual, Jeju Island, Korea, Republic of Duration: 14 Dec 2020 → 18 Dec 2020

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2020-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	59th IEEE Conference on Decision and Control, CDC 2020
Country/Territory	Korea, Republic of
City	Virtual, Jeju Island
Period	14/12/20 → 18/12/20

Access to Document

10.1109/CDC42340.2020.9304134

Cite this

Moser, T., & Lohmann, B. (2020). A New Riemannian Framework for Efficient H2-Optimal Model Reduction of Port-Hamiltonian Systems. In 2020 59th IEEE Conference on Decision and Control, CDC 2020 (pp. 5043-5049). Article 9304134 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2020-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC42340.2020.9304134

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title = "A New Riemannian Framework for Efficient H2-Optimal Model Reduction of Port-Hamiltonian Systems",

abstract = "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.",

author = "Tim Moser and Boris Lohmann",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 59th IEEE Conference on Decision and Control, CDC 2020 ; Conference date: 14-12-2020 Through 18-12-2020",

year = "2020",

month = dec,

day = "14",

doi = "10.1109/CDC42340.2020.9304134",

language = "English",

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Moser, T & Lohmann, B 2020, A New Riemannian Framework for Efficient H2-Optimal Model Reduction of Port-Hamiltonian Systems. in 2020 59th IEEE Conference on Decision and Control, CDC 2020., 9304134, Proceedings of the IEEE Conference on Decision and Control, vol. 2020-December, Institute of Electrical and Electronics Engineers Inc., pp. 5043-5049, 59th IEEE Conference on Decision and Control, CDC 2020, Virtual, Jeju Island, Korea, Republic of, 14/12/20. https://doi.org/10.1109/CDC42340.2020.9304134

A New Riemannian Framework for Efficient H2-Optimal Model Reduction of Port-Hamiltonian Systems. / Moser, Tim; Lohmann, Boris.
2020 59th IEEE Conference on Decision and Control, CDC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 5043-5049 9304134 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2020-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lohmann, Boris

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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.

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DO - 10.1109/CDC42340.2020.9304134

M3 - Conference contribution

AN - SCOPUS:85099883197

T3 - Proceedings of the IEEE Conference on Decision and Control

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

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