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Dynamic Average Consensus over Strongly Connected Digraphs Based on Integral Surplus

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This article addresses the design of a dynamic average consensus (DAC) algorithm over strongly connected but may not necessarily balanced digraphs, which seems to be the first time in the literature. Specifically, a new concept of integral surplus is proposed for DAC problems. On this basis, an integral surplus DAC algorithm is developed for agents to track the average of their multiple dynamic input signals with a bounded steady-state error. Such error is tunable by some algorithm parameters and even vanishes for special classes of input signals. Simulation examples are presented to verify the theoretical results. © 1963-2012 IEEE.
Original languageEnglish
Pages (from-to)8329-8336
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume70
Issue number12
Online published30 Jun 2025
DOIs
Publication statusPublished - Dec 2025

Funding

This work was supported in part by the National Natural Science Foundation of China through Grant No. 62422315, and in part by the Natural Science Basic Research Program of Shaanxi through Grant No. 2025JC-YBMS-667. (Corresponding author: Yongfang Liu) Runhua Cao, Yongfang Liu and Yu Zhao are with the School of Automation, Northwestern Polytechnical University, Xi’an 710129, China. (e-mail: [email protected]; [email protected]; [email protected]).

Research Keywords

  • Dynamic average consensus
  • integral surplus
  • multi-agent system
  • strongly connected digraph
  • Dynamic average consensus (DAC)
  • multiagent system

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