Multi-targets Formation Tracking for Lipschitz-Type Nonlinear Systems via Event-Triggered Scheme

Wenfei Zhang, Haiqing Li, Yangyang Zhao, Luqi Jing, Yu Zhao

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

Abstract

This paper investigates the multi-targets formation tracking (MTFT) problem for multiple autonomous agents described by Lipschitz-type nonlinear dynamics. The objective is to facilitate the formation of the desired time-varying configuration among locally connected agents, and enable them to track the convex hull of multiple targets. Specifically, each agent is granted the flexibility to explore an appropriate number of targets, contingent upon its individual capability. Without requiring the continuous interactions among agents, an event-triggered MTFT algorithm is designed to reduce the communication consumption. By leveraging the principles of Lyapunov stability theory, it is substantiated that the MTFT problem can be resolved through the proposed algorithm. Finally, a numerical example is presented to further illustrate its effectiveness.

Original languageEnglish
Title of host publicationProceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Guidance Technologies
EditorsGuo-Ping Jiang, Mengyi Wang, Zhang Ren
PublisherSpringer Science and Business Media Deutschland GmbH
Pages263-274
Number of pages12
ISBN (Print)9789819733392
DOIs
StatePublished - 2024
Event7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023 - Nanjing, China
Duration: 24 Nov 202327 Nov 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1204 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023
Country/TerritoryChina
CityNanjing
Period24/11/2327/11/23

Keywords

  • Event-Triggered Algorithm
  • Lipschitz-Type Nonlinear Systems
  • Multi-Targets Formation Tracking

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