一致性策略，作为分布式协调控制技术的基础，被广泛应用于互联网，通信，军事等各个领域。然而，随着网络节点数目的快速增长以及网络拓扑的日益复杂，仅基于节点间相对状态差值的经典一致性策略已不能完全满足现有系统的性能需求。针对目前网络大多具有若干个类似于基站/路由等分中心节点的特点，本项目通过将节点分组，利用分中心节点所包含的组群信息，经组内节点信息交互与组间组群通信并行的方式，建立基于组群化网络的一致性控制策略。构造线性系统及具有特定模型的两类非线性系统的一致性策略，利用代数图论与稳定性定理分析系统的收敛条件；建立基于组群化一致性策略的收敛速度表达式，讨论分组策略对收敛速度的影响，并利用均方法分析大规模节点随机网络的收敛情况；最后通过搭建多智能小车实验平台，对所提策略进行验证。本课题预期的研究成果是提出一种基于组群化网络一致性策略的理论架构，并使之适用于更多的多智能体网络应用。

Consensus, as the basis of distributed multi-agent cooperative system, is widely used in the Internet, communications, military and other fields. However, the classical consensus strategy based on the relative node (agent) state can not fully meet the performance requirements of modern systems due to the rapid growth of network node numbers and the increasing complexity of network topology. As most networks have sub-center nodes such like base station or route, this project divides the nodes into several groups, providing a hierarchical networks consensus strategy based on group information. The project plans to use algebraic graph theory and stability theory to solve the linear system and two kinds of specific non-linear systems. The project also establishes the convergence rate expression based on group information, and discusses the influence by group partition. In addition, mean square is used to analyze the convergence rate of the large-scale stochastic networks. Finally, a muti-UGV experimental platform is built to validate the modified consensus strategy. The expected results will propose theoretical architecture based on hierarchical networks consensus strategy via group information, such that it can be applied to many more multi-autonomous networks applications.