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Consensus Analysis of Multiagent Networks via Aggregated and Pinning Approaches

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3 Author(s)
Wenjun Xiong ; Dept. of Math., City Univ. of Hong Kong, Kowloon, China ; Ho, D.W.C. ; Zidong Wang

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.

Published in:

Neural Networks, IEEE Transactions on  (Volume:22 ,  Issue: 8 )