A discrete-time flocking algorithm for agents with sampled-data double-integrator dynamics

Brandon J. Wellman, Jesse B. Hoagg

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

5 Scopus citations

Abstract

We present a multi-agent control method that addresses flocking in discrete time. The method is decentralized, that is, each agent's controller relies on local sensing to determine the relative positions and velocities of nearby agents. Each agent has the discrete-time double-integrator dynamics obtained by sampling the continuous-time double integrator and applying a zero-order hold on the control input. We demonstrate with analysis and simulations that agents using the discrete-time flocking method converge to a set of flocking formations.

Original languageEnglish
Title of host publication2017 American Control Conference, ACC 2017
Pages1334-1339
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2017 American Control Conference, ACC 2017
Country/TerritoryUnited States
CitySeattle
Period5/24/175/26/17

Bibliographical note

Funding Information:
This work is supported in part by the National Science Foundation (OIA-1539070) and the National Aeronautics and Space Administration (NNX10AL96) through the NASA Kentucky Space Grant.

Publisher Copyright:
© 2017 American Automatic Control Council (AACC).

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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