Iterative Learning Formation Control for Multi-agent Systems with Randomly Varying Trial Lengths

  • Yimin Fan
  • , Yang Liu*
  • , Na Wang
  • *Corresponding author for this work

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

Abstract

The formation control problem of iterative learning system with stochastic variable lengths is studied. In particular, we establish an iterative learning control protocol for multi-agent system with switching topology, in which a new formation state error is proposed to deal with different lengths. Using the redefined-norm and mathematical expectation, the convergence conditions are derived. The simulation results show that the method is effective.

Original languageEnglish
Title of host publicationProceedings of 2020 Chinese Intelligent Systems Conference - Volume I
EditorsYingmin Jia, Weicun Zhang, Yongling Fu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages136-144
Number of pages9
ISBN (Print)9789811584497
DOIs
StatePublished - 2021
EventChinese Intelligent Systems Conference, CISC 2020 - Shenzhen, China
Duration: 24 Oct 202025 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume705 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceChinese Intelligent Systems Conference, CISC 2020
Country/TerritoryChina
CityShenzhen
Period24/10/2025/10/20

Keywords

  • Control protocol
  • Different lengths
  • Iterative Learning Control (ILC)
  • Multi-agent formation system

Fingerprint

Dive into the research topics of 'Iterative Learning Formation Control for Multi-agent Systems with Randomly Varying Trial Lengths'. Together they form a unique fingerprint.

Cite this