Control of coupled oscillator networks with application to microgrid technologies
arXiv:1501.00612 · doi:10.1126/sciadv.1500339
Abstract
The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies we study here control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions--a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. Interestingly, the amount of control, i.e., number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.
References in corpus (7)
- Synchronization in complex networks
- Low Dimensional Behavior of Large Systems of Globally Coupled Oscillators
- Control centrality and hierarchical structure in complex networks
- Emergence of bimodality in controlling complex networks
- Network Controllability Is Determined by the Density of Low In-Degree and Out-Degree Nodes
- Rescuing ecosystems from extinction cascades through compensatory perturbations
- Erosion of synchronization in networks of coupled oscillators
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