A Novel Clustering Method Based on Quasi-Consensus Motions of Dynamical Multiagent Systems

Abstract EN

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.