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Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter

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Abstract

This paper addresses the problem of Faut Detection and Diagnosis (FDD) of a quadrotor helicopter system in the presence of actuator faults. To this end a Two-Stage Kalman Filter (TSKF) is used to simultaneously estimate and isolate possible faults in each actuator. The faults are modelled as losses in control effectiveness of rotors. Three fault scenarios are investigated: loss of control effectiveness in one single actuator, simultaneous loss of control effectiveness in all motors, and loss of control effectiveness in three motors with different magnitudes. The developed FDD algorithm is evaluated through experimental application to an unmanned quadrotor helicopter testbed available at the Department of Mechanical and Industrial Engineering of Concordia University, called Qball-X4. The obtained results show the effectiveness of the proposed FDD method.

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Authors and Affiliations

  1. Department of Mechanical and Industrial Engineering, Concordia University, 1455 Maisonneuve Blvd. West, Montreal, QC, Canada, H3G 1M8

    M. Hadi Amoozgar, Abbas Chamseddine & Youmin Zhang

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  1. M. Hadi Amoozgar
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  2. Abbas Chamseddine
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  3. Youmin Zhang
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Correspondence to Youmin Zhang.

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Amoozgar, M.H., Chamseddine, A. & Zhang, Y. Experimental Test of a Two-Stage Kalman Filter for Actuator Fault Detection and Diagnosis of an Unmanned Quadrotor Helicopter. J Intell Robot Syst 70, 107–117 (2013). https://doi.org/10.1007/s10846-012-9757-7

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  • DOI: https://doi.org/10.1007/s10846-012-9757-7

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