Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems

Agus Ismail Hasan; Vincent Klyverts Tofterup; Kjeld Jensen

doi:10.1109/ICUAS.2019.8798308

Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems

Agus Ismail Hasan^*, Vincent Klyverts Tofterup, Kjeld Jensen

^*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

Abstract

This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure,
the experiment results demonstrate the effectiveness of the approach.

Originalsprog	Engelsk
Titel	Proceedings of the International Conference on Unmanned Aircraft Systems, ICUAS
Forlag	IEEE
Publikationsdato	15. aug. 2019
Sider	406-412
ISBN (Trykt)	978-1-7281-0334-1
ISBN (Elektronisk)	978-1-7281-0333-4, 978-1-7281-0332-7
DOI	https://doi.org/10.1109/ICUAS.2019.8798308
Status	Udgivet - 15. aug. 2019
Begivenhed	2019 International Conference on Unmanned Aircraft Systems - Atlanta Marriott Buckhead Hotel & Conference Center, Atlanta, USA Varighed: 11. jun. 2019 → 14. jun. 2019 Konferencens nummer: 229 http://www.uasconferences.com/

Konference

Konference	2019 International Conference on Unmanned Aircraft Systems
Nummer	229
Lokation	Atlanta Marriott Buckhead Hotel & Conference Center
Land/Område	USA
By	Atlanta
Periode	11/06/2019 → 14/06/2019
Internetadresse	http://www.uasconferences.com/

Dokumenter og links

10.1109/ICUAS.2019.8798308

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Citationsformater

@inproceedings{8336b5dbd6d84e9fb9077ae5fddf6a10,

title = "Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems",

abstract = "This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure,the experiment results demonstrate the effectiveness of the approach.",

author = "Hasan, {Agus Ismail} and Tofterup, {Vincent Klyverts} and Kjeld Jensen",

year = "2019",

month = aug,

day = "15",

doi = "10.1109/ICUAS.2019.8798308",

language = "English",

isbn = "978-1-7281-0334-1",

pages = "406--412",

booktitle = "Proceedings of the International Conference on Unmanned Aircraft Systems, ICUAS",

publisher = "IEEE",

address = "United States",

note = "2019 International Conference on Unmanned Aircraft Systems, ICUAS 2019 ; Conference date: 11-06-2019 Through 14-06-2019",

url = "http://www.uasconferences.com/",

}

Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems. / Hasan, Agus Ismail; Tofterup, Vincent Klyverts; Jensen, Kjeld.
Proceedings of the International Conference on Unmanned Aircraft Systems, ICUAS. IEEE, 2019. s. 406-412.

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

TY - GEN

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AU - Tofterup, Vincent Klyverts

AU - Jensen, Kjeld

N1 - Conference code: 229

PY - 2019/8/15

Y1 - 2019/8/15

N2 - This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure,the experiment results demonstrate the effectiveness of the approach.

AB - This paper presents development of model-based fail-safe modules for autonomous multirotor Unmanned Aerial Vehicles (UAVs) with safety parachute systems. The module is based on the adaptive eXogenous Kalman filter for actuator fault diagnosis. We assume all states can be measured, such that the primary goal of the filter is not the state estimation from the measurements, but the accurate reconstruction of the multirotor dynamics in real-time. Numerical simulations show the proposed diagnostic filter can be used to estimate the magnitude of the actuator faults accurately. Furthermore, based on simulated and real data recorded during a hexacopter UAV flight when its actuators experiencing complete failure,the experiment results demonstrate the effectiveness of the approach.

U2 - 10.1109/ICUAS.2019.8798308

DO - 10.1109/ICUAS.2019.8798308

M3 - Article in proceedings

SN - 978-1-7281-0334-1

SP - 406

EP - 412

BT - Proceedings of the International Conference on Unmanned Aircraft Systems, ICUAS

PB - IEEE

T2 - 2019 International Conference on Unmanned Aircraft Systems

Y2 - 11 June 2019 through 14 June 2019

ER -

Model-Based Fail-Safe Module for Autonomous Multirotor UAVs with Parachute Systems

Abstract

Konference

Dokumenter og links

Fingeraftryk

Relaterede projekter

Healthcare cargo and person transportation drones

FreeD: Free the Drones

Citationsformater