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Global and local performance metric with inertia effects

Authors

Li,  Qiang
External Organizations;

/persons/resource/Paul.Schultz

Schultz,  Paul
Potsdam Institute for Climate Impact Research;

Lin,  Wei
External Organizations;

/persons/resource/Juergen.Kurths

Kurths,  Jürgen
Potsdam Institute for Climate Impact Research;

Ji,  Peng
External Organizations;

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Citation

Li, Q., Schultz, P., Lin, W., Kurths, J., Ji, P. (2020): Global and local performance metric with inertia effects. - Nonlinear Dynamics, 102, 2, 653-665.
https://doi.org/10.1007/s11071-020-05872-4


Cite as: https://publications.pik-potsdam.de/pubman/item/item_24477
Abstract
A complex system’s structural-dynamical interplay plays a profound role in determining its collective behavior. Irregular behavior in the form of macroscopic chaos, for instance, can be potentially exhibited by the Kuramoto model of coupled phase oscillators at intermediate coupling strength with frequency assortativity and this behavior is theoretically interesting. In practice, however, such irregular behavior is often not under control and is undesired for the system’s functioning. How the underlying structural and oscillators’ dynamical interplay affects a collective phenomenon (and its corresponding stability) after being subjected to disturbances, attracts great attention. Here, we exploit the concept of a coherency performance metric, as a sum of phase differences and frequency displacements, to evaluate the response to perturbations on network-coupled oscillators. We derive the performance metric as a quadratic form of the eigenvalues and eigenmodes corresponding to the unperturbed system and the perturbation vector, and analyze the influences of perturbation direction as well as strength on the metric. We further apply a computational approach to obtain the performance metric’s derivative with respect to the oscillators’ inertia. We finally extend the metric to a local definition which reflects the pairwise casual effects between any two oscillators. These results deepen the understanding of the combined effects of the structural (eigenmodes) and dynamical (inertia) effects on the system stability.