Barrier function-based adaptive nonsingular fast terminal sliding mode control for disturbed UAVs

M. Labbadi, Hashim A. Hashim, A. E.E. Eltoukhy, M. Djemai

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The present paper investigates a new adaptive controller for the second nonlinear systems subject to disturbances. The proposed controller combines a nonsingular fast terminal sliding-mode control (NFTSMC) and an adaptive approach. The adaptive law is based on barrier function (BF). The proposed controller is applied to quadrotor whose disturbances are bounded unknown. The singularity problem is avoided because derivatives of terms with fractional powers do not appear in the control law. Without overestimating the control gain, the suggested adaptive mechanism based on BF ensures a good convergence of the output system and maintains it in a preset region of zero, regardless of the upper bound of the disturbance. A methodology design of the proposed control method for the uncertain quadrotor system is presented. Simulations validate the suggested BF-based adaptive NFTSMC (BF-ANFTSMC).

Original languageEnglish
Title of host publication2022 European Control Conference, ECC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages975-980
Number of pages6
ISBN (Electronic)9783907144077
ISBN (Print)9781665497336
DOIs
Publication statusPublished - Jul 2022
Event2022 European Control Conference, ECC 2022 - London, United Kingdom
Duration: 12 Jul 202215 Jul 2022

Publication series

Name2022 European Control Conference, ECC 2022

Conference

Conference2022 European Control Conference, ECC 2022
Country/TerritoryUnited Kingdom
CityLondon
Period12/07/2215/07/22

Keywords

  • Adaptive control
  • Barrier functions
  • Nonsingular fast terminal sliding mode
  • Quadrotor

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Systems Engineering
  • Control and Optimization
  • Modelling and Simulation

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