Name: On reduced input-output dynamic mode decomposition
Keywords: Optimization and Control (math.OC), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Mathematics - Numerical Analysis, Systems and Control (eess.SY), Numerical Analysis (math.NA), 93B30, 90C99, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 27 Feb 2018Embargo end date: 01 Jan 2017 Germany English Publisher:Springer Science and Business Media LLCJournal:Advances in Computational Mathematics, volume 44, pages 1,751-1,768 (issn: 1019-7168, eissn: 1572-9044,

Authors: Peter Benner; Christian Himpe; Tim Mitchell;

doi: 10.1007/s10444-018-9592-x , 10.48550/arxiv.1712.08447

arXiv: http://arxiv.org/abs/1712.08447

handle: 21.11116/0000-0002-8D27-4 , 21.11116/0000-0000-2C02-D

On reduced input-output dynamic mode decomposition

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Abstract

The identification of reduced-order models from high-dimensional data is a challenging task, and even more so if the identified system should not only be suitable for a certain data set, but generally approximate the input-output behavior of the data source. In this work, we consider the input-output dynamic mode decomposition method for system identification. We compare excitation approaches for the data-driven identification process and describe an optimization-based stabilization strategy for the identified systems.

Country

Germany

Related Organizations

Max Planck Society
Germany
Max Planck Institute for Dynamics of Complex Technical Systems
Germany

Keywords

Optimization and Control (math.OC), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Mathematics - Numerical Analysis, Systems and Control (eess.SY), Numerical Analysis (math.NA), 93B30, 90C99, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control

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