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Adaptive neural network tracking control of multi-agent systems with state constraints

  • Dongyu Li
  • , Guangfu Ma
  • , Chuangjiang Li
  • , Wei Zhang
  • , Wei He

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

Abstract

This paper studies the distributed coordinated tracking problem for multiple Euler-Lagrange systems (MELSs) with full-state constraints. Firstly, a distributed finite-time sliding-mode estimator (DFSE) is introduced to access precise estimations of the leader's position and velocity. Then, to guarantee the full-state constraints of MELSs, we use the barrier Lyapunov function (BLF) technique and a Moore-Penrose inverse term to design a distributed coordinated tracking control law. The asymptotic convergence of all the state errors can be proofed by Lyapunov stability analysis. Finally, simulation results are given to illustrate the feasibility of the proposed control law.

Original languageEnglish
Title of host publicationProceedings - 2017 Chinese Automation Congress, CAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages201-205
Number of pages5
ISBN (Electronic)9781538635247
DOIs
StatePublished - 29 Dec 2017
Externally publishedYes
Event2017 Chinese Automation Congress, CAC 2017 - Jinan, China
Duration: 20 Oct 201722 Oct 2017

Publication series

NameProceedings - 2017 Chinese Automation Congress, CAC 2017
Volume2017-January

Conference

Conference2017 Chinese Automation Congress, CAC 2017
Country/TerritoryChina
CityJinan
Period20/10/1722/10/17

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