Attitude Estimation of a Quadcopter with one fully damaged rotor using on-board MARG Sensors

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Quadcopters are becoming increasingly popular across diverse sectors. Since rotor damages occur frequently, it is essential to improve the attitude estimation and thus ultimately the ability to control a damaged quadcopter. This research is based on a state-of-the-art method that makes it possible to control the quadcopter despite the total failure of a single rotor, where the attitude and position of the quadcopter are provided by an external system. In the present research, a novel attitude estimator called Adaptive Fuzzy Complementary Kalman Filter (AFCKF) has been developed and validated that works independently of any external systems. It is able to estimate the attitude of a quadcopter with one fully damaged rotor while only relying on the on-board MARG (Magnetometer, Accelerometer, Rate Gyroscope) sensors. The AFCKF provides significantly better attitude estimates for flights with a damaged rotor than mainstream filters, estimating the roll and pitch of the quadcopter with an RMS error of less than 1.7 degrees and a variance of less than 2 degrees. The proposed filter also provides accurate yaw estimates despite the fast spinning motion of the damaged quadcopter, and thus outperforms existing methods at the cost of only a small increase in computation.
Original languageEnglish
Title of host publicationAIAA SCITECH 2022 Forum
Number of pages8
ISBN (Electronic)978-1-62410-631-6
Publication statusPublished - 2022
EventAIAA SCITECH 2022 Forum - virtual event
Duration: 3 Jan 20227 Jan 2022

Publication series

NameAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022


ConferenceAIAA SCITECH 2022 Forum


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