A submodular optimization framework for leader selection in linear multi-agent systems

Andrew Clark, Radha Poovendran

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

42 Scopus citations

Abstract

A broad class of multi-agent systems are leader-follower systems, in which the states of a set of leader agents are used to influence the states of the remaining agents. In this paper, we study the problem of choosing specific agents that will act as leaders in order to optimize system performance. We show that for a diverse set of networked multi-agent systems, including systems with constant and time-varying topologies, the leader selection problem can be studied using a submodular optimization framework. We further show that the problems of choosing a predefined number of leader nodes, as well as choosing both the number and specific nodes to satisfy a performance requirement, can be formulated within the proposed submodular optimization framework. We derive analytical performance bounds for the proposed solutions for linear multi-agent systems with static as well as time-varying network topologies. Numerical illustration is provided for the proposed approach.

Original languageEnglish
Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3614-3621
Number of pages8
ISBN (Print)9781612848006
DOIs
StatePublished - 2011
Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
Duration: Dec 12 2011Dec 15 2011

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
Country/TerritoryUnited States
CityOrlando, FL
Period12/12/1112/15/11

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