Experimental validation of fault detection and diagnosis for unmanned aerial vehicles

Abstract

This chapter investigates the problems of fault detection, diagnosis, and fault-tolerant control for unmanned aerial vehicles (UAVs). It presents first a detailed overview on the existing experimental works considering these problems in the literature. The existing works consider fixed-wing as well as rotorcraft UAVs including the single-rotor and the multi-rotor helicopters (also known as quadrotors). Later on, the chapter discusses three Kalman filters employed for actuator fault detection and diagnosis, namely, the unscented Kalman filter, the two-stage Kalman filter, and the adaptive two-stage Kalman filter. The three filters are experimentally applied to a quadrotor helicopter UAV test bed at the Department of Mechanical and Industrial Engineering of Concordia University. The obtained results are shown, compared, and discussed.