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arXiv 1705.00537eess.SYcs.SY
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具有时间变化交互的系统共识分析:一种事件触发方法

Consensus analysis of systems with time-varying interactions : An event-triggered approach

Indian Institute of Technology Bombay(印度理工学院孟买分校);Max Planck Institute for Dynamics of Complex Technical Systems(复杂技术系统动力学马克斯·普朗克研究所)

S. Arun Kumar, N. R. Chowdhury, S. Srikant, J. Raisch

AI总结:

研究时间变化图下多智能体系统在事件触发控制下的共识行为,分析静态与动态触发函数对状态收敛的影响,并通过仿真验证切换拓扑下的结果。

摘要:

我们提出了在事件触发控制范式下,具有单积分器动力学并通过时间变化图交互的系统共识分析。事件触发控制稀疏化控制应用,从而减少控制努力。首先,我们考虑具有持续激励交互的多智能体系统,并研究事件触发控制下的行为,使用两种触发函数类型——静态触发和动态触发。我们显示,在静态触发情况下,边状态收敛到原点附近的一个球体,而动态触发函数迫使状态以指数方式达到共识。最后,我们将这些结果扩展到更一般的情况下,考虑切换拓扑。我们显示,对于通过切换拓扑交互的智能体,可以得到类似的结果,并通过仿真验证我们的结果。

英文摘要:

We present consensus analysis of systems with single integrator dynamics interacting via time-varying graphs under the event-triggered control paradigm. Event-triggered control sparsifies the control applied, thus reducing the control effort expended. Initially, we consider a multi-agent system with persistently exciting interactions and study the behaviour under the application of event-triggered control with two types of trigger functions- static and dynamic trigger.We show that while in the case of static trigger, the edge-states converge to a ball around the origin, the dynamic trigger function forces the states to reach consensus exponentially. Finally, we extend these results to a more general setting where we consider switching topologies. We show that similar results can be obtained for agents interacting via switching topologies and validate our results by means of simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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