带有通信量化和延时的多智能体系统一致性研究

Recently, multi-agent networks have been widely studied due to their broad application such as sensor networks, Unmanned Air Vehicles (UAV) formations, congestion control in communication networks and so on. The main focus of studying multi-agent networks is on how consensus has emerged as a result of local interactions among agents. In real multi-agent network, information flow between two neighboring agents is generally affected by many uncertain factors including limited communication capacity, network induced time delay and so on. The aforementioned communication constraint should be considered in the design of control strategy or algorithms. In this proposal, we investigate the networked multi-agent consensus problems under quantized information and time delays. Functional differential equations with discontinuous right-hand side will be established to describe the dynamic of the multi-agent system with quantization and time delays. Differential inclusions, non-smooth analysis theory, Lyapunov-Krasovskii stability theory and algebraic graph theory will be employed to quantitative analyze consensus or/and finite-time consensus of discontinuous systems and the algorithm which has better robustness and convergence speed will be designed.

近年来，网络化的多智能体系统成为数学领域的一个前沿课题，并且越來越多的被广泛应用到分布式传感器网络、卫星的姿态控制以及通讯网络的拥塞控制等各個领域。许多协调控制问题都可以用多智能体网络的一致性(consensus)理论来建模,即基于局部信息交换的多智能体系统如何达到相同的状态。在真实的网络环境下，多智能体在信息传输时不可避免的要受到通信带宽以及延时的影响。在设计多智能体系统一致性算法时应充分考虑这些因素。为此，本项目将首先建立一个右端不连续的泛函微分方程来刻画带有量化和延时的多智能体网络；运用非光滑分析，微分包含、稳定性理论、代数图论等手段来研究量化、延时与系统一致性和收敛速度之间的定量关系。进而设计出具有更强鲁棒性和更快收敛速度的一致性算法。

近年来，网络化的多智能体系统成为数学领域的一个前沿课题，并且越來越多的被广泛应用到分布式传感器网络、卫星的姿态控制以及通讯网络的拥塞控制等各個领域。许多协调控制问题都可以用多智能体网络的一致性(consensus)理论来建模,即基于局部信息交换的多智能体系统如何达到相同的状态。在真实的网络环境下，多智能体在信息传输时不可避免的要受到通信带宽以及延时的影响。在设计多智能体系统一致性算法时应充分考虑这些因素。为此，本项目将运用非光滑分析，微分包含、稳定性理论、代数图论等手段来研究量化、延时与系统一致性和收敛速度之间的定量关系。进而设计出具有更强鲁棒性和更快收敛速度的一致性算法。