Fixed-Time Consensus for High-Order Multi-Agent Systems with Nonlinear Uncertainties and Disturbances via Event-Triggered Control

Yani Zhang, Feng Pan, Rongxin Cui, Xinxin Guo, Shouxu Zhang

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

Abstract

This paper delves into the fixed-time consensus tracking problem within high-order multi-agent systems characterized by unknown uncertainties and disturbances. To mitigate the impact of unknown terms, we leverage the approximation capabilities of RBF neural networks to approximate the nonlinear uncertainties and design disturbance observers to estimate external disturbances. To reserve communication and computing resource utilization, we propose a fixed-time event-triggered controller and validate that the systems avoid exhibiting Zeno behavior. Ultimately, the efficacy of our proposed approach is substantiated through simulation.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Development and Learning, ICDL 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages127-132
Number of pages6
ISBN (Electronic)9781665470759
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Development and Learning, ICDL 2023 - Macau, China
Duration: 9 Nov 202311 Nov 2023

Publication series

Name2023 IEEE International Conference on Development and Learning, ICDL 2023

Conference

Conference2023 IEEE International Conference on Development and Learning, ICDL 2023
Country/TerritoryChina
CityMacau
Period9/11/2311/11/23

Keywords

  • consensus
  • disturbance observer
  • event-triggered
  • fixed-time

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