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Electrical Engineering and Systems Science > Systems and Control

arXiv:2212.00455 (eess)
[Submitted on 1 Dec 2022 ]

Title: Consensus of hierarchical multi-agent systems with a time-varying set of active agents

Title: 具有时变活动代理集的分层多智能体系统的共识

Authors:Victor Daniel Reyes Dreke, Mircea Lazar
Abstract: Time-varying hierarchical multi-agent systems are common in many applications. A well-known solution to control these systems is to use state feedback controllers that depend on the adjacency matrix to reach consensus. This solution has been applied so far to multi-agent systems with fixed or time-varying communication topologies. In this paper, we consider single-integrator multi-agent systems where only a subset of the agents are active at any given time and the set of active agents is time-varying. This type of multi-agent system is relevant in applications such as modular multilevel converters and water pumping systems. We develop a switching algorithm that periodically selects a set of active agents through a set of graphs that connect the follower agents with a leader agent. We further prove that the developed switching algorithm combined with a classic consensus protocol yields convergence to a consensus state defined by the leader despite a time-varying set of active agents. The effectiveness of the switching algorithm is illustrated in two benchmark examples: a modular multilevel converter and a water pumping system.
Abstract: 时变分层多智能体系统在许多应用中都很常见。 控制这些系统的知名解决方案之一是使用依赖于邻接矩阵的状态反馈控制器以达到一致性。 到目前为止,这种解决方案已应用于具有固定或时变通信拓扑的多智能体系统。 本文考虑了一类单积分器多智能体系统,其中在任意给定时刻仅有一部分智能体处于活动状态,并且活跃智能体集是时变的。 这种类型的多智能体系统与模块化多电平变换器和水泵系统等应用相关。 我们开发了一种切换算法,该算法通过一组图周期性地选择一组活跃智能体,这些图将跟随智能体与领导智能体连接。 此外,我们进一步证明,结合经典一致性协议的所开发的切换算法能够在活跃智能体集时变的情况下收敛到由领导智能体定义的一致状态。 切换算法的有效性在两个基准示例中得到了展示:模块化多电平变换器和水泵系统。
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2212.00455 [eess.SY]
  (or arXiv:2212.00455v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2212.00455
arXiv-issued DOI via DataCite

Submission history

From: Victor Daniel Resyes Dreke [view email]
[v1] Thu, 1 Dec 2022 12:12:34 UTC (25,784 KB)
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