Skip to main navigation Skip to search Skip to main content

Adaptive backstepping based consensus tracking of uncertain nonlinear systems with event-triggered communication

  • Wei Wang
  • , Jiang Long
  • , Jing Zhou
  • , Jiangshuai Huang*
  • , Changyun Wen
  • *Corresponding author for this work
  • Beihang University
  • University of Agder
  • Chongqing University
  • Nanyang Technological University

Research output: Contribution to journal › Article › peer-review

Abstract

This paper investigates the consensus tracking problem for a class of uncertain high-order nonlinear systems with parametric uncertainties and event-triggered communication. Under a directed communication condition, a totally distributed adaptive backstepping based control scheme is presented. Specifically, a decentralized triggering condition is adopted in this paper such that continuous monitoring of neighboring states, as required in some existing results, can be avoided. Besides, to handle the non-differentiability problem of virtual controllers, which arises from the utilization of neighboring states collected only at the triggering instants, the virtual controllers in each recursive step are firstly designed with continuous communication. Then, the partial derivatives of these designed virtual controllers are adopted to construct distributed adaptive consensus controllers for the event based communication case. It is shown that with the presented distributed adaptive consensus control scheme and even-triggered communication mechanism, all the closed-loop signals are uniformly bounded and the output consensus tracking errors will converge to a compact set. Besides, the tracking performance in the mean square sense can be improved by appropriately adjusting design parameters.

Original languageEnglish
Article number109841
JournalAutomatica
Volume133
DOIs
StatePublished - Nov 2021

Keywords

  • Consensus
  • Distributed adaptive control
  • Event-triggered communication
  • Uncertain high-order nonlinear systems

Fingerprint

Dive into the research topics of 'Adaptive backstepping based consensus tracking of uncertain nonlinear systems with event-triggered communication'. Together they form a unique fingerprint.

Cite this