Design of adaptive neural fuzzy formation controller for multi-robot systems

  • Yeong Hwa Chang*
  • , Wei Shou Chan
  • , Cheng Yuan Yang
  • , Chia Wen Chang
  • , Tzu Chi Chung
  • *Corresponding author for this work

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

1 Scopus citations

Abstract

This paper aims to investigate the formation control of multi-robot systems, where the first-order kinematic model of a differential wheeled robot is considered. Based on the graph theory and consensus algorithm, an adaptive neural fuzzy formation controller is designed with the capability of on-line learning. The learning rules of controller parameters can be derived from the analyzing of Lyapunov stability. Simulations are adopted to verify the feasibility of proposed techniques. From simulation results, the proposed adaptive neural fuzzy controller can provide better formation responses compared to conventional consensus algorithm.

Original languageEnglish
Title of host publication2012 American Control Conference, ACC 2012
Pages3161-3166
Number of pages6
StatePublished - 2012
Event2012 American Control Conference, ACC 2012 - Montreal, QC, Canada
Duration: 27 06 201229 06 2012

Publication series

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

Conference

Conference2012 American Control Conference, ACC 2012
Country/TerritoryCanada
CityMontreal, QC
Period27/06/1229/06/12

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