多智能体系统在分布式采样控制下的动力学行为

本文运用图论、矩阵分析和现代控制理论等工具, 研究信息网络传输下多智能体系统的协调控制和动力学行为. 假设每个智能体通过数字化网络传感器获得其邻近智能体的位置状态,而且多智能体系统采取分布式线性控制协议. 每个智能体被描述为一个简单的采样系统,多智能体系统转化为混合动力学系统. 研究结果表明,多智能体系统所呈现的渐近聚集、周期振荡和发散动力学行为不仅和网络结构的代数特征有关, 而且和每个智能体的动力学方程、采样周期有关. 本文给出了具体精确的代数判据. 仿真例子进一步验证了本文结果的有效性.

Dynamic Behavior of Multi-agent Systems with Distributed Sampled Control

This paper devotes to the study of coordinated control and dynamical behavior of multi-agent systems in digital communication network by means of graph theory, matrix analysis, and control theory. It is assumed that each agent of the system is described by a sampling dynamical system and is able to obtain the information of location coordinates of its neighbors by remote sensors. The system behavior depends on a linear distributed protocol in digital communication network. Thus, the whole multi-agent system can be considered as a hybrid dynamic system. Our results show that the multi-agent systems under consideration may appear three different dynamical behaviors, i.e., asymptotical aggregation, periodic oscillation, and divergence of agents. The dynamical behavior of the system depends not only on the algebraic characterization of the network topology but also on the dynamics of agents, as well as the sampling time period. Moreover, we give some algebraic criteria relevant to the system behavior. Examples show the effectiveness of our results.