Finite-time synchronization of complex dynamical networks with multi-links via intermittent controls

Mingwen Zheng, Lixiang Li (), Haipeng Peng, Jinghua Xiao, Yixian Yang, Hui Zhao and Jingfeng Ren
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Mingwen Zheng: School of Science, Beijing University of Posts and Telecommunications
Lixiang Li: Information Security Center, State Key Laboratory of Networking and Switching Technology, National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications
Haipeng Peng: Information Security Center, State Key Laboratory of Networking and Switching Technology, National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications
Jinghua Xiao: School of Science, Beijing University of Posts and Telecommunications
Yixian Yang: Information Security Center, State Key Laboratory of Networking and Switching Technology, National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications
Hui Zhao: School of Science, Beijing University of Posts and Telecommunications
Jingfeng Ren: Information Security Center, State Key Laboratory of Networking and Switching Technology, National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications

The European Physical Journal B: Condensed Matter and Complex Systems, 2016, vol. 89, issue 2, 1-12

Abstract: Abstract This paper considers finite-time synchronization of complex multi-links dynamical networks with or without internal time delays via intermittent controls. Two simple intermittent feedback controllers are designed to achieve finite-time synchronization between the drive and response system. Some novel and effective finite-time synchronization criteria are derived based on finite-time stability analysis techniques. By constructing suitable Lyapunov functions, we theoretically prove its correctness. Finally, two numerical simulation examples are given to show the effectiveness of proposed method in this paper.

Keywords: Statistical; and; Nonlinear; Physics (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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DOI: 10.1140/epjb/e2016-60935-7

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