Skip to main navigation Skip to search Skip to main content

An IT2FNN-Based Sliding Mode Control Approach to Formation of Multi-Agent Systems with Switching Topology

  • School of Astronautics, Harbin Institute of Technology

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

Abstract

This paper deals with the problem of robust formation control for multi-agent systems with switching topology by using a new fuzzy-neural-network based sliding mode control (SMC). A second-order nonlinear multi-agent system with uncertain velocity dynamics is formulated. In terms of the uncertain velocity dynamics term, we use an type-2 fuzzy-neural-network to obtain its estimate, then an integrated SMC law based on an newly designed integral sliding variable is proposed to the formation control multi-agent systems. Besides, the convergence analysis of the formation tracking error is provided. Moreover, the analysis of the finite-time reachability of a practical sliding mode is presented based on the Lyapunov function approach. Eventually, simulation results are given to show the validity of the proposed control approach.

Original languageEnglish
Title of host publicationProceedings of the 41st Chinese Control Conference, CCC 2022
EditorsZhijun Li, Jian Sun
PublisherIEEE Computer Society
Pages5050-5055
Number of pages6
ISBN (Electronic)9789887581536
DOIs
StatePublished - 2022
Externally publishedYes
Event41st Chinese Control Conference, CCC 2022 - Hefei, China
Duration: 25 Jul 202227 Jul 2022

Publication series

NameChinese Control Conference, CCC
Volume2022-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference41st Chinese Control Conference, CCC 2022
Country/TerritoryChina
CityHefei
Period25/07/2227/07/22

Keywords

  • Multi-agent systems
  • formation control
  • fuzzy neural network
  • sliding mode control
  • switching topology

Fingerprint

Dive into the research topics of 'An IT2FNN-Based Sliding Mode Control Approach to Formation of Multi-Agent Systems with Switching Topology'. Together they form a unique fingerprint.

Cite this