Fault detection using Upper Bound Interval Kalman Filter for unmaned aerial vehicle

This paper deals with dynamics estimation and fault detection of unmaned aerial vehicles (uav) using the Upper Bound Interval Kalman Filter (UBIKF). An upper bound for all positive semi-definite matrices included in an interval matrix is calculated. This upper bound is used to generate envelopes for the variables to be estimated which are the dynamics of the UAV. It allows to provide a guaranteed estimation envelope for the considered dynamics. Then, the fault detection scheme is used based on a $\chi^{2}$ test. The faults concern sensors and actuators. Simulations on a discrete uncertain UAV model highlight the efficiency of the proposed filter for both UAV dynamics estimation and fault detection.