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- W4225133399 abstract "Network dynamical systems are often characterized by the interlaced evolution of the node and edge dynamics, which are driven by both deterministic and stochastic factors. This manuscript offers a general mathematical model of coevolving network, which associates a state variable to each node and edge in the network, and describes their evolution through coupled stochastic differential equations. We study the emergence of synchronization, be it spontaneous or induced by a pinning control action, and provide sufficient conditions for local and global convergence. We enable the use of the Master Stability Function approach for studying coevolving networks, thereby obtaining conditions for almost sure local exponential convergence, whereas global conditions are derived using a Lyapunov-based approach. The theoretical results are then leveraged to design synchronization and pinning control protocols in two select applications. In the first one, the edge dynamics are tailored to induce spontaneous synchronization, whereas in the second the pinning edges are activated/deactivated and their weights modulated to drive the network towards the pinner’s trajectory in a distributed fashion." @default.
- W4225133399 created "2022-05-01" @default.
- W4225133399 creator A5067896804 @default.
- W4225133399 creator A5078340993 @default.
- W4225133399 date "2022-01-01" @default.
- W4225133399 modified "2023-09-28" @default.
- W4225133399 title "Synchronization and pinning control of stochastic coevolving networks" @default.
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- W4225133399 doi "https://doi.org/10.1016/j.arcontrol.2022.04.005" @default.
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