Pinning Synchronization of Complex Dynamical Networks on Time Scales

Fang-di, Kong; Sun, Jian-Ping

doi:10.1007/s12555-020-0041-5

Cited by 10 publications

(1 citation statement)

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“…E. N. Sanchez et alused recurrent high order neural networks to identify system parameters [16]. F.-D. Kong and J.-P. Suninvestigated the synchronization problem of complex dynamical networks on time scales, but the problem how to determine the number of pinned nodes is still unsolved [17].…”

Section: Introductionmentioning

confidence: 99%

Topology Uniformity Pinning Control for Multi-agent Flocking

Liu

2022

Preprint

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The optimal pinning node selection for multi-agent flocking is a NP-hard problem. The current pinning node selection strategies mainly depend on complex network node characteristics which are lack of rigorous mathematical proof for flocking control. This paper studies the effect and selection strategy of pinning node based on matrix eigenvalue theory. Firstly, the effect on the eigenvalue of Laplacian matrix by pinning node is analyzed. Secondly, the synchronization index which reflects topology uniformity of multi-agent system is proposed to exert maximum influence on the system synchronizability. A practicable optimal pinning node selection method based on synchronization index is proposed and analyzed by the eigenvalue perturbation method. Finally, the simulations show the rate of system convergence by using optimal synchronizability pinning node is better than the maximum degree centrality.

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Section: Introductionmentioning

confidence: 99%