Leader-Following Cluster Consensus of Multiagent Systems With Measurement Noise and Weighted Cooperative-Competitive Networks

Leader-following cluster consensus is investigated for multiagent systems with weighted cooperative-competitive networks and measurement noise. A stochastic approximation protocol is proposed for interactively balanced and sub-balanced networks, and pinning control is introduced to deal with the divergence phenomenon in interactively unbalanced networks. With these protocols, sufficient conditions for reaching a strong mean-square leader-following cluster consensus are established for all the three types of networks, which are also extended to the cases without measurement noise. Numerical examples illustrate the effectiveness of the proposed protocols and theoretical analysis.

Automated summary

This paper investigates the leader-following cluster consensus problem for multiagent systems with weighted cooperative-competitive networks and measurement noise. The proposed protocols and theoretical analysis demonstrate their effectiveness in different types of networks. Numerical examples provide further evidence.