Observer-Based Consensus for Multiagent Systems Under Stochastic Sampling Mechanism
研究了随机采样间隔下多智能体系统的一致性问题，设计了基于邻居相对输出信息的全阶和降阶观测器，并给出了保证均方一致性的充分条件。
This paper is concerned with the consensus problem of general linear dynamic multiagent systems with stochastic sampling. In this paper, the sampling intervals randomly switch between two different values. The communication topology between agents is fixed and directed. Full- and reduced-order observers are designed based on neighbor agents' relative output information. The algorithms to construct such observers are also provided. By using the estimated states of the agents, the observer-based consensus protocol with stochastic sampling are presented. Sufficient conditions to ensure consensus in mean square are derived by using Lyapunov stability theory. Finally, simulations are given to examine the effectiveness of the proposed methods.