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Title: Consensus analysis of multiagent networks via aggregated and pinning approaches
Authors: Xiong, W
Wang, Z
Keywords: Absolute consensus;Lie algebra;Directed networks;Graph Laplacian;Node-and-node pinning method;Pinning consensus
Issue Date: 2011
Publisher: IEEE
Citation: IEEE Transactions on Neural Networks, 22(8): 1231 - 1240, Aug 2011
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.
Description: This is the post-print version of of the Article - Copyright @ 2011 IEEE
ISSN: 1045-9227
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

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