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International Symposium on Neural Networks

ISNN 2019: Advances in Neural Networks – ISNN 2019 pp 101–110Cite as

A Novel Second-Order Consensus Control in Multi-agent Dynamical Systems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11555))

Abstract

In this paper, a new type protocol is proposed. Second-order consensus in multi-agent dynamical systems with this protocol is studied using a new analytical method. A necessary and sufficient condition for reaching consensus of the system with the this protocol is obtained, which depending on the spectrum of the Laplacian matrix and the control parameter setting. Meanwhile, a simple and practical criterion of sampling period is given in the ordinary case. Finally, two simulation examples are given to verify and illustrate the theoretical analysis.

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Acknowledgements

The work is supported by the Natural Science Foundation of China under Grant 61603129, 61841301, the Natural Science Foundation of Hubei Province under Grant 2016CFC734.

Author information

Authors and Affiliations

  1. College of Mathematics and Statistics, Hubei Normal University, Huangshi, 435002, China

    Boshan Chen

  2. College of Computer Science and Technnology, Hubei Normal University, Huangshi, 435002, China

    Jiejie Chen

  3. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Zhigang Zeng

  4. Computer School, Hubei Polytechnic University, Huangshi, 435002, China

    Ping Jiang

Authors
  1. Boshan Chen
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  2. Jiejie Chen
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  3. Zhigang Zeng
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  4. Ping Jiang
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Corresponding author

Correspondence to Jiejie Chen .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. Sichuan University, Chengdu, China

    Huajin Tang

  3. Northeastern University, Shenyang, China

    Zhanshan Wang

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Chen, B., Chen, J., Zeng, Z., Jiang, P. (2019). A Novel Second-Order Consensus Control in Multi-agent Dynamical Systems. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11555. Springer, Cham. https://doi.org/10.1007/978-3-030-22808-8_11

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  • DOI: https://doi.org/10.1007/978-3-030-22808-8_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22807-1

  • Online ISBN: 978-3-030-22808-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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