Adaptive Fuzzy Control for Multi-Agent Systems With Unknown Measurement Sensitivity via a Simplified Backstepping Approach

Zhixu Du, Hongjing Liang, Choon Ki Ahn

Research output: Contribution to journalArticlepeer-review

Abstract

This brief investigates the adaptive tracking control problem for a class of nonlinear multi-agent systems with unknown measurement sensitivity using a simplified backstepping approach. By introducing Nussbaum gain, a new approach is proposed that effectively relaxes the restrictive condition that the unknown measurement sensitivity be within a particular range. A simplified backstepping approach is then presented to alleviate the structural complexity and high computational costs. It is proven that the tracking error converges to a small neighborhood of the origin and that all of the signals are bounded. Finally, simulation analysis is conducted to verify the effectiveness of the proposed control strategy.

Original languageEnglish
Pages (from-to)2862-2866
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Volume69
Issue number6
DOIs
Publication statusPublished - 2022 Jun 1

Keywords

  • Fuzzy control
  • simplified backstepping approach
  • unknown measurement sensitivity

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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