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A Novel Clustering Method Based on Quasi-Consensus Motions of Dynamical Multiagent Systems

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  • Ning Cai
  • Chen Diao
  • M. Junaid Khan

Abstract

This paper presents a novel approach for clustering, which is based on quasi-consensus of dynamical linear high-order multiagent systems. The graph topology is associated with a selected multiagent system, with each agent corresponding to one vertex. In order to reveal the cluster structure, the agents belonging to a similar cluster are expected to aggregate together. To establish the theoretical foundation, a necessary and sufficient condition is given to check the achievement of group consensus. Two numerical instances are furnished to illustrate the results of our approach.

Suggested Citation

  • Ning Cai & Chen Diao & M. Junaid Khan, 2017. "A Novel Clustering Method Based on Quasi-Consensus Motions of Dynamical Multiagent Systems," Complexity, Hindawi, vol. 2017, pages 1-8, September.
    • Handle: RePEc:hin:complx:4978613
    DOI: 10.1155/2017/4978613
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    References listed on IDEAS

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    1. Dong, Lei & Wang, Lijie & Khahro, Shahnawaz Farhan & Gao, Shuang & Liao, Xiaozhong, 2016. "Wind power day-ahead prediction with cluster analysis of NWP," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1206-1212.
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    Cited by:

    1. Jijun Qu & Zhijian Ji & Chong Lin & Haisheng Yu, 2018. "Fast Consensus Seeking on Networks with Antagonistic Interactions," Complexity, Hindawi, vol. 2018, pages 1-15, December.

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