Control surfaces fault detection and isolation for an unmanned aerial vehicle

François Bateman; Hassan Noura; Mustapha Ouladsine

Control surfaces fault detection and isolation for an unmanned aerial vehicle

François Bateman, Hassan Noura, Mustapha Ouladsine

Department of Electrical and Communication Engineering

Research output: Contribution to conference › Paper › peer-review

1 Citation (Scopus)

Abstract

In this paper a fault detection and isolation method (FDI) for an Unmanned Aerial Vehicle (UAV) is presented. The proposed method deals with control surface failures while the aircraft is equipped with an autopilot. This method does not require the complete model of the system. Fault detection consists of exciting judiciously actuators and analyzing cross-correlations between measurements. The temporal and frequential properties of the signal are analyzed during transient of the failure. From this point of view, a wavelet analysis has been implemented to isolate the faulty control surfaces.

Original language	English
Pages	145-150
Number of pages	6
Publication status	Published - 2007
Event	3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007 - Buenos Aires, Argentina Duration: Feb 8 2007 → Feb 10 2007

Other

Other	3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007
Country/Territory	Argentina
City	Buenos Aires
Period	2/8/07 → 2/10/07

ASJC Scopus subject areas

Automotive Engineering
Control and Systems Engineering
Safety, Risk, Reliability and Quality

Cite this

Bateman, F., Noura, H., & Ouladsine, M. (2007). Control surfaces fault detection and isolation for an unmanned aerial vehicle. 145-150. Paper presented at 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007, Buenos Aires, Argentina.

Control surfaces fault detection and isolation for an unmanned aerial vehicle. / Bateman, François; Noura, Hassan; Ouladsine, Mustapha.
2007. 145-150 Paper presented at 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007, Buenos Aires, Argentina.

Research output: Contribution to conference › Paper › peer-review

Bateman, F, Noura, H & Ouladsine, M 2007, 'Control surfaces fault detection and isolation for an unmanned aerial vehicle', Paper presented at 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007, Buenos Aires, Argentina, 2/8/07 - 2/10/07 pp. 145-150.

Bateman F, Noura H, Ouladsine M. Control surfaces fault detection and isolation for an unmanned aerial vehicle. 2007. Paper presented at 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007, Buenos Aires, Argentina.

Bateman, François ; Noura, Hassan ; Ouladsine, Mustapha. / Control surfaces fault detection and isolation for an unmanned aerial vehicle. Paper presented at 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007, Buenos Aires, Argentina.6 p.

@conference{3159786e6c384a9a8954d27f0f1d9b1a,

title = "Control surfaces fault detection and isolation for an unmanned aerial vehicle",

abstract = "In this paper a fault detection and isolation method (FDI) for an Unmanned Aerial Vehicle (UAV) is presented. The proposed method deals with control surface failures while the aircraft is equipped with an autopilot. This method does not require the complete model of the system. Fault detection consists of exciting judiciously actuators and analyzing cross-correlations between measurements. The temporal and frequential properties of the signal are analyzed during transient of the failure. From this point of view, a wavelet analysis has been implemented to isolate the faulty control surfaces.",

author = "Fran{\c c}ois Bateman and Hassan Noura and Mustapha Ouladsine",

year = "2007",

language = "English",

pages = "145--150",

note = "3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007 ; Conference date: 08-02-2007 Through 10-02-2007",

}

TY - CONF

T1 - Control surfaces fault detection and isolation for an unmanned aerial vehicle

AU - Bateman, François

AU - Noura, Hassan

AU - Ouladsine, Mustapha

PY - 2007

Y1 - 2007

N2 - In this paper a fault detection and isolation method (FDI) for an Unmanned Aerial Vehicle (UAV) is presented. The proposed method deals with control surface failures while the aircraft is equipped with an autopilot. This method does not require the complete model of the system. Fault detection consists of exciting judiciously actuators and analyzing cross-correlations between measurements. The temporal and frequential properties of the signal are analyzed during transient of the failure. From this point of view, a wavelet analysis has been implemented to isolate the faulty control surfaces.

AB - In this paper a fault detection and isolation method (FDI) for an Unmanned Aerial Vehicle (UAV) is presented. The proposed method deals with control surface failures while the aircraft is equipped with an autopilot. This method does not require the complete model of the system. Fault detection consists of exciting judiciously actuators and analyzing cross-correlations between measurements. The temporal and frequential properties of the signal are analyzed during transient of the failure. From this point of view, a wavelet analysis has been implemented to isolate the faulty control surfaces.

UR - http://www.scopus.com/inward/record.url?scp=84900020115&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84900020115&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84900020115

SP - 145

EP - 150

T2 - 3rd International Conference on Advances in Vehicle Control and Safety 2007, AVCS 2007 and 3rd International Conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2007, Held at the IMSM 2007

Y2 - 8 February 2007 through 10 February 2007

ER -

Control surfaces fault detection and isolation for an unmanned aerial vehicle

Abstract

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this