1 research outputs found
Cluster synchronization of diffusively-coupled nonlinear systems: A contraction based approach
Finding the conditions that foster synchronization in networked oscillatory
systems is critical to understanding a wide range of biological and mechanical
systems. However, the conditions proved in the literature for synchronization
in nonlinear systems with linear coupling, such as has been used to model
neuronal networks, are in general not strict enough to accurately determine the
system behavior. We leverage contraction theory to derive new sufficient
conditions for cluster synchronization in terms of the network structure, for a
network where the intrinsic nonlinear dynamics of each node may differ. Our
result requires that network connections satisfy a cluster-input-equivalence
condition, and we explore the influence of this requirement on network
dynamics. For application to networks of nodes with neuronal spiking dynamics,
we show that our new sufficient condition is tighter than those found in
previous analyses which used nonsmooth Lyapunov functions. Improving the
analytical conditions for when cluster synchronization will occur based on
network configuration is a significant step toward facilitating understanding
and control of complex oscillatory systems