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arXiv 1808.01418eess.SYcs.SY
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基于图滤波的平均一致性:新方法、明确收敛速率和最优设计

Average Consensus by Graph Filtering: New Approach, Explicit Convergence Rate and Optimal Design

Wuhan University of Science and Technology(武汉科技大学);Swinburne University of Technology(斯威本科技大学)

Jingwen Yi, Li Chai, Jingxin Zhang

AI总结:

本文从图信号处理角度重新审视多智能体一致性问题,提出基于图谱滤波的新型分析与设计方法,推导出有限时间与渐近平均一致性的充分必要条件,建立一致性收敛速率与周期一致性协议的直接联系,并提出多项式设计图谱滤波器的方法。

摘要:

本文从图信号处理角度重新审视多智能体一致性问题。将一致性协议描述为图谱滤波器,提出在不确定网络中分析和设计一致性协议的新方法,该方法难以用现有时域方法处理。本文新方法得到以下结果:1)多智能体系统的有限时间和渐近平均一致性的充分必要条件。2)一致性收敛速率与周期一致性协议的直接联系。3)将快速一致性问题转化为图谱滤波器的多项式设计问题。4)为不确定图上的多智能体系统设计周期一致性协议的拉格朗日多项式插值方法和最坏情况最优插值方法。5)设计协议的收敛速率的显式公式。给出了若干数值例子以验证这些结果的有效性、有效性和优势。

英文摘要:

This paper revisits the problem of multi-agent consensus from a graph signal processing perspective. Describing a consensus protocol as a graph spectrum filter, we present an effective new approach to the analysis and design of consensus protocols in the graph spectrum domain for the uncertain networks, which are difficult to handle by the existing time-domain methods. This novel approach has led to the following new results in this paper: 1) New necessary and sufficient conditions for both finite-time and asymptotic average consensus of multi-agent systems. 2) Direct link between the consensus convergence rate and the periodic consensus protocols. 3) Conversion of the fast consensus problem to the problem of polynomial design of graph spectrum filter. 4) A Lagrange polynomial interpolation method and a worst-case optimal interpolation method for the design of periodic consensus protocols for the MASs on uncertain graphs. 5) Explicit formulas for the convergence rate of the designed protocols. Several numerical examples are given to demonstrate the validity, effectiveness and advantages of these results.

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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