Model-based techniques for virtual sensing of longitudinal flight parameters

Georges Hardier; Cédric Seren; Pierre Ezerzere

International Journal of Applied Mathematics and Computer Science (2015)

  • Volume: 25, Issue: 1, page 23-38
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Georges Hardier, Cédric Seren, and Pierre Ezerzere. "Model-based techniques for virtual sensing of longitudinal flight parameters." International Journal of Applied Mathematics and Computer Science 25.1 (2015): 23-38. <http://eudml.org/doc/270626>.

@article{GeorgesHardier2015,
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.},
author = {Georges Hardier, Cédric Seren, Pierre Ezerzere},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {model-based estimation; fault detection; virtual sensor; Kalman filtering; surrogate modeling},
language = {eng},
number = {1},
pages = {23-38},
title = {Model-based techniques for virtual sensing of longitudinal flight parameters},
url = {http://eudml.org/doc/270626},
volume = {25},
year = {2015},
}

TY - JOUR
AU - Georges Hardier
AU - Cédric Seren
AU - Pierre Ezerzere
TI - Model-based techniques for virtual sensing of longitudinal flight parameters
JO - International Journal of Applied Mathematics and Computer Science
PY - 2015
VL - 25
IS - 1
SP - 23
EP - 38
AB - 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.
LA - eng
KW - model-based estimation; fault detection; virtual sensor; Kalman filtering; surrogate modeling
UR - http://eudml.org/doc/270626
ER -

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