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  Stability of synchronization systems with inertia against frequency perturbations

Ye, J., Ji, P., Zlatić, V., Grin, A., Zhao, Y., Kurths, J. (2025): Stability of synchronization systems with inertia against frequency perturbations. - Chaos, 35, 10, 103142.
https://doi.org/10.1063/5.0281703

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 Creators:
Ye, Jiachen1, Author
Ji, Peng1, Author
Zlatić, Vinko1, Author
Grin, Alexander1, Author
Zhao, Yanbin1, Author
Kurths, Jürgen2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Synchronization phenomena are widely observed in nature, human society, and engineering systems composed of interacting elements. Several systems, in particular power grids, require synchronization to maintain normal operational functionality, which imposes higher demands on system stability. Much effort has been devoted to exploring the underlying mechanism of such crucial phenomena, by taking the classical Kuramoto model as an ideal object of theoretical research. The introduction of an inertia term, while enriching synchronization behaviors and enabling better description of real systems, significantly increases the analytical complexity of the model and thereby requires deeper investigation. Here, we study the stability of the Kuramoto model with inertia against various types of frequency perturbation. Using the fragility performance metric as the quantitative indicator of stability, we reveal how dynamical parameters and spectral characteristics of the network interact and jointly influence the system stability against perturbations. We also show the intrinsic difference of system stability arising from network structures, which could be counteracted by a rapid vibration of the decay perturbation, an interesting phenomenon we term the “rapid vibration effect.”

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Language(s): eng - English
 Dates: 2025-10-232025-10-23
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1063/5.0281703
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
 Degree: -

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Title: Chaos
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 35 (10) Sequence Number: 103142 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/180808
Publisher: American Institute of Physics (AIP)