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Institute of Electrical and Electronics Engineers, IEEE Transactions on Neural Networks, 8(22), p. 1231-1240, 2011

DOI: 10.1109/tnn.2011.2157938

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Consensus Analysis of Multiagent Networks via Aggregated and Pinning Approaches

Journal article published in 2011 by Wenjun Xiong, Zidong Wang ORCID, Daniel W. C. Ho, Zidong Wang ORCID
This paper is available in a repository.
This paper is available in a repository.

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Abstract

In this paper, the consensus problem of multiagent nonlinear directed networks (MNDNs) is discussed in the case that a MNDN does not have a spanning tree to reach the consensus of all nodes. By using the Lie algebra theory, a linear node-and-node pinning method is proposed to achieve a consensus of a MNDN for all nonlinear functions satisfying a given set of conditions. Based on some optimal algorithms, large-size networks are aggregated to small-size ones. Then, by applying the principle minor theory to the small-size networks, a sufficient condition is given to reduce the number of controlled nodes. Finally, simulation results are given to illustrate the effectiveness of the developed criteria.