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Event-Triggering Sampling Based Synchronization of Delayed Complex Dynamical Networks: An M-matrix Approach

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Advances in Neural Networks - ISNN 2017 (ISNN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10261))

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Abstract

In this technical note, the synchronization problem is investigated for delayed complex dynamical networks. A novel distributed event-triggered sampling rule is proposed, i.e., one node can decide its own event time via its own state value and the state values of its neighbor agents as long as the locally-computed error exceeds the given state-dependent threshold. The aim here is to design controllers and some required events such that the considered complex dynamical networks can achieve synchronization. Then the M-matrix method is applied to derive some criteria in the form of eigenvalue-based inequality for achieving the synchronization, and the Zeno behavior can be avoided as well. Finally, a numerical example is presented for demonstrating the availability and effectiveness of the main results.

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Acknowledgments

This paper was supported by the National Natural Science Foundation of China (Grant No. 61673176).

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Authors and Affiliations

  1. The Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

    Yang Tang

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  1. Yang Tang
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Correspondence to Yang Tang .

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Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Tang, Y. (2017). Event-Triggering Sampling Based Synchronization of Delayed Complex Dynamical Networks: An M-matrix Approach. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10261. Springer, Cham. https://doi.org/10.1007/978-3-319-59072-1_56

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  • DOI: https://doi.org/10.1007/978-3-319-59072-1_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59071-4

  • Online ISBN: 978-3-319-59072-1

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