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Model-based Fault Detection and Identification of a Quadrotor with Rotor Fault

Model-based Fault Detection and Identification of a Quadrotor with Rotor Fault Fault detection and identification (FDI) is a challenging and critical process when dealing with nonlinear, unstable, and underactuated systems such as multirotor. This article presents a novel two-stage structure for a fault-tolerant FDI approach for a quadrotor with an actuator fault. The FDI algorithm generates residual signals for fault detection using a model-based approach based on the parity space. The basic idea behind this approach is to leverage measurement coherence by generating residuals via linear combinations of measurement outputs and control inputs over a finite window. The parity vector is generated using the states of the faulty system, which have been filtered using an extended Kalman filter, the inputs, and the healthy quadrotor model. To detect and identify the actuator's partial fault, the residual signal is examined using the exponential forgetting factor recursive least square method. Real-time testbed experiments are used to determine the FDI algorithm's performance and to demonstrate the proposed algorithm's effectiveness in identifying a quadrotor's rotor fault. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Aeronautical and Space Sciences Springer Journals

Model-based Fault Detection and Identification of a Quadrotor with Rotor Fault

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References (37)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to The Korean Society for Aeronautical & Space Sciences 2022
ISSN
2093-274X
eISSN
2093-2480
DOI
10.1007/s42405-022-00494-z
Publisher site
See Article on Publisher Site

Abstract

Fault detection and identification (FDI) is a challenging and critical process when dealing with nonlinear, unstable, and underactuated systems such as multirotor. This article presents a novel two-stage structure for a fault-tolerant FDI approach for a quadrotor with an actuator fault. The FDI algorithm generates residual signals for fault detection using a model-based approach based on the parity space. The basic idea behind this approach is to leverage measurement coherence by generating residuals via linear combinations of measurement outputs and control inputs over a finite window. The parity vector is generated using the states of the faulty system, which have been filtered using an extended Kalman filter, the inputs, and the healthy quadrotor model. To detect and identify the actuator's partial fault, the residual signal is examined using the exponential forgetting factor recursive least square method. Real-time testbed experiments are used to determine the FDI algorithm's performance and to demonstrate the proposed algorithm's effectiveness in identifying a quadrotor's rotor fault.

Journal

International Journal of Aeronautical and Space Sciences – Springer Journals

Published: Nov 1, 2022

Keywords: Fault detection and identification; Residual signal; Recursive least square; Rotor fault

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