An adaptive Extended Kalman Filter for monitoring and estimating key aircraft flight parameters

This paper addresses the selection and the monitoring of some key flight parameters along with their estimation in nominal and degraded flight conditions including faulty sensors situations. Anticipating more availability of flight parameters for future aircraft, isolating faulty measurements and reconstructing through time the missing signals is a challenging objective for Flight Control Systems, especially because some of them are essential for control purposes. To this end, this paper proposes a solution based on virtual sensors which make use of an Adaptive Extended Kalman Filter supplemented by dedicated Fault Detection and Isolation algorithm. It provides the ability for the longitudinal flight parameters of a civil aircraft to be estimated on-line before and after the occurrence of one or several failures. To facilitate onboard implementation, the main aerodynamic coefficients are approximated by a set of surrogate models. The proposed approach offers interesting monitoring capabilities including the detection of common mode failures (i.e., simultaneous failures occurring on redundant sensors). Real flight data involving strong atmospheric perturbations, 3-axis winds and successive faults on the static and total pressure probes from the take-off to the cruise is shown to evaluate the performances of the approach in terms of detection, isolation, estimation and reconfiguration capabilities