A Novel Clustering Method Based on Quasi-Consensus Motions of Dynamical Multiagent Systems
Ning Cai, Chen Diao, Muhammad Junaid Khan · Complexity · 2017
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.