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Circuits, Systems, and Signal Processing

, Volume 33, Issue 6, pp 1721–1736 | Cite as

Improved Weighted Average Prediction for Multi-Agent Networks

  • Huiwei WangEmail author
  • Xiaofeng Liao
  • Tingwen Huang
  • Chaojie Li
Article

Abstract

In sense of communication delays, an improved robust consensus algorithm for multi-agent networks and its the convergence rate have been investigated in this paper. Precisely, an improved weighted average prediction has been introduced to reformulate the network model into a neutral network fashion. By virtue of analyzing the Hopf bifurcation, an upper bound of the communication delay is derived for the multi-agent network, which could guarantee the network to achieve weighted average consensus. In addition, the main results show that not only can the proposed method promote the robustness but also improve its convergence rate. Finally, two numerical simulations are provided, which demonstrates the effectiveness of the method.

Keywords

Convergence speed Multi-agent networks Robustness Weighted average consensus 

Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61170249 and Grant 61273021, in part by the Research Fund of Preferential Development Domain for the Doctoral Program of Ministry of Education of China under Grant 201101911130005, in part by the State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, under Grant 2007DA10512709207, in part by the Natural Science Foundation Project of CQ cstc2013jjB40008, and in part by the Program for Changjiang Scholars. This publication was made possible by NPRP Grant #4-1162-1-181 from the Qatar National Research Fund (a member of the Qatar Foundation).

The statements made herein are solely the responsibility of the authors.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Huiwei Wang
    • 1
    Email author
  • Xiaofeng Liao
    • 1
  • Tingwen Huang
    • 2
  • Chaojie Li
    • 3
  1. 1.State Key Laboratory of Power Transmission Equipment & System Security and New Technology, College of Computer ScienceChongqing UniversityChongqingP.R. China
  2. 2.Texas A&M University at QatarDohaQatar
  3. 3.School of Science, Information Technology and EngineeringUniversity of BallaratMt HelenAustralia

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