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Enhancing consensus in weighted networks with coupling time-delay

Author

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  • Ning, Bo
  • Ren, Quansheng
  • Zhao, Jianye

Abstract

We study the consensus problem in a weighted and directed network composed of self-propelled agents. The weight which quantifies the relationship between the agents is adjusted according to their state incoherence to suppress the heterogeneity in state. The proposed consensus protocol enhances the convergence efficiency of consensus greatly and has better performance than that of two other protocols. The convergence efficiency can be further improved by adjusting the parameter of this protocol. Furthermore, the robustness of the system against coupling time-delay is significantly increased. Unlike most consensus acceleration methods, no topological information is needed in our model. Networks with different stuctures are investigated to demonstrate the generality of the method.

Suggested Citation

  • Ning, Bo & Ren, Quansheng & Zhao, Jianye, 2012. "Enhancing consensus in weighted networks with coupling time-delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3061-3068.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:11:p:3061-3068
    DOI: 10.1016/j.physa.2011.12.057
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    References listed on IDEAS

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    1. Lin, Peng & Jia, Yingmin, 2008. "Average consensus in networks of multi-agents with both switching topology and coupling time-delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 303-313.
    2. Chen, Zhuo & Gao, Jianxi & Cai, Yunze & Xu, Xiaoming, 2011. "Evolution of cooperation among mobile agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(9), pages 1615-1622.
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    Cited by:

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    2. Shang, Lihui & Xu, Zhiqiang, 2023. "Adaptive control strategy improves synchronization of self-propelled agents," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    3. Wu, Zhihai & Peng, Li & Xie, Linbo & Wen, Jiwei, 2013. "Stochastic bounded consensus tracking of leader–follower multi-agent systems with measurement noises based on sampled-data with small sampling delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 918-928.

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