On multi-agent self-tuning consensus

Miloje Radenkovic, Tamal Bose

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

This paper considers the consensus problem in complex networks of uncertain discrete time agents. The coupling parameters among agents are locally self tuned by least-mean square (LMS) algorithm, without using any global information. In this process each agent minimizes a local cost function dependent on the error between the agent state and the average of neighbors states. Provided that the network graph is strongly connected, it is shown that for each agent the sequence of coupling parameters is convergent, and all agent states converge toward the same constant value. It is demonstrated that in the face of unknown high-frequency gain, the proposed algorithms generate such coupling parameters so that the overall multi-agent system is marginally stable with only one pole on the unit circle, located at λ=1.

Original languageEnglish (US)
Pages (from-to)46-54
Number of pages9
JournalAutomatica
Volume55
DOIs
StatePublished - May 1 2015

Fingerprint

Tuning
Complex networks
Multi agent systems
Cost functions
Poles

Keywords

  • Adaptive consensus
  • Cooperative control
  • Multi-agent systems
  • Self-adjusting systems
  • Synchronization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

On multi-agent self-tuning consensus. / Radenkovic, Miloje; Bose, Tamal.

In: Automatica, Vol. 55, 01.05.2015, p. 46-54.

Research output: Contribution to journalArticle

Radenkovic, Miloje ; Bose, Tamal. / On multi-agent self-tuning consensus. In: Automatica. 2015 ; Vol. 55. pp. 46-54.
@article{5b53b34b062448669e1a13fa8f262f10,
title = "On multi-agent self-tuning consensus",
abstract = "This paper considers the consensus problem in complex networks of uncertain discrete time agents. The coupling parameters among agents are locally self tuned by least-mean square (LMS) algorithm, without using any global information. In this process each agent minimizes a local cost function dependent on the error between the agent state and the average of neighbors states. Provided that the network graph is strongly connected, it is shown that for each agent the sequence of coupling parameters is convergent, and all agent states converge toward the same constant value. It is demonstrated that in the face of unknown high-frequency gain, the proposed algorithms generate such coupling parameters so that the overall multi-agent system is marginally stable with only one pole on the unit circle, located at λ=1.",
keywords = "Adaptive consensus, Cooperative control, Multi-agent systems, Self-adjusting systems, Synchronization",
author = "Miloje Radenkovic and Tamal Bose",
year = "2015",
month = "5",
day = "1",
doi = "10.1016/j.automatica.2015.02.025",
language = "English (US)",
volume = "55",
pages = "46--54",
journal = "Automatica",
issn = "0005-1098",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - On multi-agent self-tuning consensus

AU - Radenkovic, Miloje

AU - Bose, Tamal

PY - 2015/5/1

Y1 - 2015/5/1

N2 - This paper considers the consensus problem in complex networks of uncertain discrete time agents. The coupling parameters among agents are locally self tuned by least-mean square (LMS) algorithm, without using any global information. In this process each agent minimizes a local cost function dependent on the error between the agent state and the average of neighbors states. Provided that the network graph is strongly connected, it is shown that for each agent the sequence of coupling parameters is convergent, and all agent states converge toward the same constant value. It is demonstrated that in the face of unknown high-frequency gain, the proposed algorithms generate such coupling parameters so that the overall multi-agent system is marginally stable with only one pole on the unit circle, located at λ=1.

AB - This paper considers the consensus problem in complex networks of uncertain discrete time agents. The coupling parameters among agents are locally self tuned by least-mean square (LMS) algorithm, without using any global information. In this process each agent minimizes a local cost function dependent on the error between the agent state and the average of neighbors states. Provided that the network graph is strongly connected, it is shown that for each agent the sequence of coupling parameters is convergent, and all agent states converge toward the same constant value. It is demonstrated that in the face of unknown high-frequency gain, the proposed algorithms generate such coupling parameters so that the overall multi-agent system is marginally stable with only one pole on the unit circle, located at λ=1.

KW - Adaptive consensus

KW - Cooperative control

KW - Multi-agent systems

KW - Self-adjusting systems

KW - Synchronization

UR - http://www.scopus.com/inward/record.url?scp=84927921416&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84927921416&partnerID=8YFLogxK

U2 - 10.1016/j.automatica.2015.02.025

DO - 10.1016/j.automatica.2015.02.025

M3 - Article

AN - SCOPUS:84927921416

VL - 55

SP - 46

EP - 54

JO - Automatica

JF - Automatica

SN - 0005-1098

ER -