title: Consensus analysis of multiagent networks via aggregated and pinning approaches.
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.
authors: Department of Mathematics, City University of Hong Kong, Kowloon, Hong Kong. xwenjun2@gmail.com
authors: Wenjun
authors: W
authors: Xiong
authors: Daniel W C
authors: DW
authors: Ho
authors: Zidong
authors: Z
authors: Wang
mesh_terms: D015982:Bias; D003627:Data Interpretation, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics