Leader-Following Cluster Consensus of Multiagent Systems With Measurement Noise and Weighted Cooperative–Competitive Networks
研究了带测量噪声和加权合作竞争网络的多智能体系统如何实现领导跟随集群一致性，提出了随机逼近协议和牵制控制方法，并给出了三种网络类型下达到强均方一致性的充分条件。
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.