Fault-Tolerant Estimation of UAV Dynamics in the Presence of Sensor/Actuator Faults

Chingiz Hajiyev

doi:10.1007/978-3-031-62094-2_14

Fault-Tolerant Estimation of UAV Dynamics in the Presence of Sensor/Actuator Faults

Chingiz Hajiyev^*

^*Corresponding author for this work

Department of Aeronautical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

A new fault-tolerant estimation method of unmanned aerial vehicle (UAV) dynamics in the presence of sensor/actuator faults with both adaptivity and robustness is proposed. This chapter addresses the subject of making a choice between the adaptive and robust methods when sensor/actuator faults occur. An adaptive method with Q-adaptation and robust method with R-adaptation are presented. Fault detection in the Kalman filter is based on the chi-square distribution of the normalized quadratic innovation function (NQI). After the detection of faults, it is proposed to run simultaneously both R-adaptive and Q-adaptive Kalman filters and compare their estimation performances to distinguish the sensor and actuator faults.

Original language	English
Title of host publication	Sustainable Aviation
Publisher	Springer Nature
Pages	97-103
Number of pages	7
DOIs	https://doi.org/10.1007/978-3-031-62094-2_14
Publication status	Published - 2025

Publication series

Name	Sustainable Aviation
Volume	Part F418
ISSN (Print)	2730-7778
ISSN (Electronic)	2730-7786

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Actuator faults
Fault-tolerant estimation
Robust adaptive Kalman filter
Sensor faults
Unmanned aerial vehicle

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10.1007/978-3-031-62094-2_14

Cite this

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abstract = "A new fault-tolerant estimation method of unmanned aerial vehicle (UAV) dynamics in the presence of sensor/actuator faults with both adaptivity and robustness is proposed. This chapter addresses the subject of making a choice between the adaptive and robust methods when sensor/actuator faults occur. An adaptive method with Q-adaptation and robust method with R-adaptation are presented. Fault detection in the Kalman filter is based on the chi-square distribution of the normalized quadratic innovation function (NQI). After the detection of faults, it is proposed to run simultaneously both R-adaptive and Q-adaptive Kalman filters and compare their estimation performances to distinguish the sensor and actuator faults.",

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ER -

Fault-Tolerant Estimation of UAV Dynamics in the Presence of Sensor/Actuator Faults

Abstract

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