Robust Fault Diagnosis for quadrotor uavs using Adaptive Thau observer

Zhaohui Cen, Hassan Noura, Tri Bagus Susilo, Younes Al Younes

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators' faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.

Original languageEnglish
Pages (from-to)573-588
Number of pages16
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Volume73
Issue number1-4
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Fingerprint

Failure analysis
Actuators
Rotors
Unmanned aerial vehicles (UAV)
Surface roughness
Experiments

Keywords

  • Adaptive Thau observer
  • Fault detection
  • Isolation and estimation
  • Quadrotor
  • Robustness

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Cite this

Robust Fault Diagnosis for quadrotor uavs using Adaptive Thau observer. / Cen, Zhaohui; Noura, Hassan; Susilo, Tri Bagus; Al Younes, Younes.

In: Journal of Intelligent and Robotic Systems: Theory and Applications, Vol. 73, No. 1-4, 01.01.2014, p. 573-588.

Research output: Contribution to journalArticle

Cen, Zhaohui ; Noura, Hassan ; Susilo, Tri Bagus ; Al Younes, Younes. / Robust Fault Diagnosis for quadrotor uavs using Adaptive Thau observer. In: Journal of Intelligent and Robotic Systems: Theory and Applications. 2014 ; Vol. 73, No. 1-4. pp. 573-588.
@article{4f7f5d165db54b578fb40bef9586f957,
title = "Robust Fault Diagnosis for quadrotor uavs using Adaptive Thau observer",
abstract = "A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators' faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.",
keywords = "Adaptive Thau observer, Fault detection, Isolation and estimation, Quadrotor, Robustness",
author = "Zhaohui Cen and Hassan Noura and Susilo, {Tri Bagus} and {Al Younes}, Younes",
year = "2014",
month = "1",
day = "1",
doi = "10.1007/s10846-013-9921-8",
language = "English",
volume = "73",
pages = "573--588",
journal = "Journal of Intelligent and Robotic Systems: Theory and Applications",
issn = "0921-0296",
publisher = "Springer Netherlands",
number = "1-4",

}

TY - JOUR

T1 - Robust Fault Diagnosis for quadrotor uavs using Adaptive Thau observer

AU - Cen, Zhaohui

AU - Noura, Hassan

AU - Susilo, Tri Bagus

AU - Al Younes, Younes

PY - 2014/1/1

Y1 - 2014/1/1

N2 - A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators' faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.

AB - A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators' faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.

KW - Adaptive Thau observer

KW - Fault detection

KW - Isolation and estimation

KW - Quadrotor

KW - Robustness

UR - http://www.scopus.com/inward/record.url?scp=84899440102&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84899440102&partnerID=8YFLogxK

U2 - 10.1007/s10846-013-9921-8

DO - 10.1007/s10846-013-9921-8

M3 - Article

AN - SCOPUS:84899440102

VL - 73

SP - 573

EP - 588

JO - Journal of Intelligent and Robotic Systems: Theory and Applications

JF - Journal of Intelligent and Robotic Systems: Theory and Applications

SN - 0921-0296

IS - 1-4

ER -