online read us now
Paper details
Number 1 - March 2015
Volume 25 - 2015
Model-based techniques for virtual sensing of longitudinal flight parameters
Georges Hardier, Cédric Seren, Pierre Ezerzere
Abstract
Introduction of fly-by-wire and increasing levels of automation significantly improve the safety of civil aircraft, and result in
advanced capabilities for detecting, protecting and optimizing A/C guidance and control. However, this higher complexity
requires the availability of some key flight parameters to be extended. Hence, the monitoring and consolidation of those
signals is a significant issue, usually achieved via many functionally redundant sensors to extend the way those parameters
are measured. This solution penalizes the overall system performance in terms of weight, maintenance, and so on. Other
alternatives rely on signal processing or model-based techniques that make a global use of all or part of the sensor data
available, supplemented by a model-based simulation of the flight mechanics. That processing achieves real-time estimates
of the critical parameters and yields dissimilar signals. Filtered and consolidated information is delivered in unfaulty
conditions by estimating an extended state vector, including wind components, and can replace failed signals in degraded
conditions. Accordingly, this paper describes two model-based approaches allowing the longitudinal flight parameters of a
civil A/C to be estimated on-line. Results are displayed to evaluate the performances in different simulated and real flight
conditions, including realistic external disturbances and modeling errors.
Keywords
model-based estimation, fault detection, virtual sensor, Kalman filtering, surrogate modeling