Volume 55, Number 2, March-April 2021
|Page(s)||561 - 594|
|Published online||31 March 2021|
On error estimation for reduced-order modeling of linear non-parametric and parametric systems
Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany
2 Fakultät für Mathematik, Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany
* Corresponding author: firstname.lastname@example.org
Accepted: 12 January 2021
Motivated by a recently proposed error estimator for the transfer function of the reduced-order model of a given linear dynamical system, we further develop more theoretical results in this work. Moreover, we propose several variants of the error estimator, and compare those variants with the existing ones both theoretically and numerically. It is shown that some of the proposed error estimators perform better than or equally well as the existing ones. All the error estimators considered can be easily extended to estimate the output error of reduced-order modeling for steady linear parametric systems.
Mathematics Subject Classification: 37M05 / 65P99 / 65L80
Key words: Model order reduction / error estimation
© EDP Sciences, SMAI 2021
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