Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies
IEEE Transactions on Mobile Computing
Distributed average consensus with least-mean-square deviation
Journal of Parallel and Distributed Computing
Brief paper: Pinning adaptive synchronization of a general complex dynamical network
Automatica (Journal of IFAC)
Criteria for global pinning-controllability of complex networks
Automatica (Journal of IFAC)
An Adaptive Energy Efficient Topology for Wireless Sensor Networks
FGCN '08 Proceedings of the 2008 Second International Conference on Future Generation Communication and Networking - Volume 02
Brief paper: Novel decentralized adaptive strategies for the synchronization of complex networks
Automatica (Journal of IFAC)
Distributed Consensus in Multi-vehicle Cooperative Control: Theory and Applications
Distributed Consensus in Multi-vehicle Cooperative Control: Theory and Applications
Cluster synchronization of linearly coupled complex networks under pinning control
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Synchronization and control of complex networks via contraction, adaptation and evolution
IEEE Circuits and Systems Magazine - Special issue on complex networks applications in circuits and systems
Hi-index | 0.00 |
In this paper, we present a novel adaptive strategy for consensus and synchronization of complex networks. The strategy is inspired by bistable phenomena that are observed in a variety of mechanical systems. The novelty is that the adaptation involves the topology of the network itself rather than its coupling gains. In particular, we model the evolution of each coupling gain as a second order dynamical system that is subject to the action of a double-well potential. Through a new mechanism, termed as edge snapping, an unweighted network topology emerges at steady state. We assess the stability properties of the proposed scheme through analytical methods and numerical investigations. We conduct an extensive numerical study of the topological properties of the emerging network to elucidate the correlation between the initial conditions of the nodes' dynamics and the network structure.