Adaptive eXogenous Kalman Filter for Actuator Fault Diagnosis in Robotics and Autonomous Systems

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Abstrakt

This paper presents an algorithm for actuator fault diagnosis in robotics and autonomous systems under random uncertainties based on a cascade of nonlinear observer and linearized Kalman filter. The two-stage estimation method assumes uniform complete observability and controllability conditions and persistent excitation condition. To this end, we consider dynamical systems of robotics and autonomous systems with one-sided Lipschitz nonlinearity. To demonstrate the effectiveness of the proposed algorithm, numerical simulations in a single-link flexible joint robot are performed.

OriginalsprogEngelsk
Titel2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019
Antal sider6
ForlagIEEE
Publikationsdato10. feb. 2020
Sider162-167
ISBN (Trykt)978-1-7281-3788-9
ISBN (Elektronisk)9781728137872
DOI
StatusUdgivet - 10. feb. 2020
Begivenhed7th IEEE International Conference on Control, Mechatronics and Automation, ICCMA 2019 - Delft, Holland
Varighed: 6. nov. 20198. nov. 2019

Konference

Konference7th IEEE International Conference on Control, Mechatronics and Automation, ICCMA 2019
LandHolland
ByDelft
Periode06/11/201908/11/2019
SponsorDelft University of Technology, IEEE
Navn2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019

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  • Citationsformater

    Hasan, A. (2020). Adaptive eXogenous Kalman Filter for Actuator Fault Diagnosis in Robotics and Autonomous Systems. I 2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019 (s. 162-167). IEEE. 2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019 https://doi.org/10.1109/ICCMA46720.2019.8988724