Resilient Delayed Impulsive Control for Consensus of Multiagent Networks Subject to Malicious Agents
提出一种基于采样数据的延迟脉冲控制策略，在无需知道恶意代理数量的情况下，实现受恶意代理影响的多智能体网络的弹性共识，并给出达成共识的图条件。
Impulsive control is widely applied to achieve the consensus of multiagent networks (MANs). It is noticed that malicious agents may have adverse effects on the global behaviors, which, however, are not taken into account in the literature. In this study, a novel delayed impulsive control strategy based on sampled data is proposed to achieve the resilient consensus of MANs subject to malicious agents. It is worth pointing out that the proposed control strategy does not require any information on the number of malicious agents, which is usually required in the existing works on resilient consensus. Under appropriate control gains and sampling period, a necessary and sufficient graphic condition is derived to achieve the resilient consensus of the considered MAN. Finally, the effectiveness of the resilient delayed impulsive control is well demonstrated via simulation studies.