H2 model reduction for diffusively coupled second-order networks by convex-optimization

doi:10.1016/j.automatica.2021.110118

H2 model reduction for diffusively coupled second-order networks by convex-optimization

2022-03-01

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Jacquelien M.A. Scherpen *

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Junlin Xiong

DOI：10.1016/j.automatica.2021.110118

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This paper provides an H-2 optimal scheme for reducing diffusively coupled second-order systems evolving over undirected networks. The aim is to find a reduced-order model that not only approximates the input-output mapping of the original system but also preserves crucial structures, such as the second-order form, asymptotically stability, and diffusive couplings. To this end, an H-2 optimal approach based on a convex relaxation is used to reduce the dimension, yielding a lower order asymptotically stable approximation of the original second-order network system. Then, a novel graph reconstruction approach is employed to convert the obtained model to a reduced system that is interpretable as an undirected diffusively coupled network. Finally, the effectiveness of the proposed method is illustrated via a large-scale networked mass-spring-damper system. (C) 2021 The Author(s). Published by Elsevier Ltd.

Keywords:

Second-order networks

Diffusive coupling

H-2 model reduction

Linear matrix inequality

Convex-optimization

H2 model reduction for diffusively coupled second-order networks by convex-optimization

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