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arXiv 2202.03012eess.SYcs.MAcs.SYmath.OC
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EDCHO:高阶精确动态一致性

EDCHO: High Order Exact Dynamic Consensus

Rodrigo Aldana-López, Rosario Aragüés, Carlos Sagüés

摘要:

本文讨论了多智能体系统中当期望的一致性数量是时变信号时的平均一致性问题。虽然这个问题已经解决了现有的文献中的线性计划,只有有界的稳态误差已经实现。其他方法已经使用一阶滑动模式来实现零稳态误差,但是遭受抖振效应。在这项工作中,我们提出了一个新的精确的动态共识算法,利用高阶滑模,在一个分布式微分器的形式,实现零稳态误差的平均时变参考信号在一组代理。此外,如果需要,我们的建议也能够实现对平均信号的高阶导数的共识。对无向连通图的EDCHO算法的稳定性和收敛性进行了深入的形式化研究。最后,我们的建议的有效性和优势显示与具体的仿真场景。

英文摘要:

This article addresses the problem of average consensus in a multi-agent system when the desired consensus quantity is a time varying signal. Although this problem has been addressed in existing literature by linear schemes, only bounded steady-state errors have been achieved. Other approaches have used first order sliding modes to achieve zero steady-state error, but suffer from the chattering effect. In this work, we propose a new exact dynamic consensus algorithm which leverages high order sliding modes, in the form of a distributed differentiator to achieve zero steady-state error of the average of time varying reference signals in a group of agents. Moreover, our proposal is also able to achieve consensus to high order derivatives of the average signal, if desired. An in depth formal study on the stability and convergence for EDCHO is provided for undirected connected graphs. Finally, the effectiveness and advantages of our proposal are shown with concrete simulation scenarios.

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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