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International Symposium on Neural Networks

ISNN 2018: Advances in Neural Networks – ISNN 2018 pp 407–414Cite as

Adaptive Consensus Tracking of First-Order Multi-agent Systems with Unknown Control Directions

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10878))

Abstract

A novel control algorithm based on Nussbaum function is proposed to settle the adaptive consensus tracking for first-order multi-agent systems with completely non-identical unknown control directions (UCDs) and uncertainties under connected undirected graphs or balanced and weakly connected digraphs in this paper. The Nussbaum function is introduced in the distributed control law to settle the UCDs of multi-agent systems. Then, it is proven that multi-agent systems with UCDs and uncertainties can achieve asymptotic consensus and reach the target state under the assumption that the underlying topology is undirected graphs or balanced and weakly connected graphs. Finally, theoretical and simulation results has verified the validity of our proposed algorithm.

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Author information

Authors and Affiliations

  1. School of Automation, Southeast University, Nanjing, China

    Yajun Zheng, Qingling Wang & Changyin Sun

Authors
  1. Yajun Zheng
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  2. Qingling Wang
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  3. Changyin Sun
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Corresponding authors

Correspondence to Qingling Wang or Changyin Sun .

Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

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Cite this paper

Zheng, Y., Wang, Q., Sun, C. (2018). Adaptive Consensus Tracking of First-Order Multi-agent Systems with Unknown Control Directions. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_47

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  • DOI: https://doi.org/10.1007/978-3-319-92537-0_47

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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