Fast Fault Detection on a Quadrotor using Onboard Sensors and a Kalman Filter Approach
This addresses safety and reliability for quadrotor operations, though it is incremental as it builds on existing Kalman filter methods.
The paper tackles fast detection of actuator failures on quadrotors by estimating effectiveness factors using onboard sensors and a Kalman filter, achieving detection delays of 30 to 130 ms with no missed detections or false alarms in tests.
This paper presents a novel method for fast and robust detection of actuator failures on quadrotors. The proposed algorithm has very little model dependency. A Kalman filter estimator estimates a stochastic effectiveness factor for every actuator, using only onboard RPM, gyro and accelerometer measurements. Then, a hypothesis test identifies the failed actuator. This algorithm is validated online in real-time, also as part of an active fault tolerant control system. Loss of actuator effectiveness is induced by ejecting the propellers from the motors. The robustness of this algorithm is further investigated offline over a range of parameter settings by replaying real flight data containing 26 propeller ejections. The detection delays are found to be in the 30 to 130 ms range, without missed detections or false alarms occurring.