This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Flight Parameter Estimation for Augmented Flight Control System Autonomy
Technical Paper
2011-01-2801
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
In the framework of the aircraft global optimization, for future and upcoming programs, current research interests include more Electrical Flight Control System (EFCS) autonomy for a more easy-to-handle aircraft. A possible solution is to increase the number of redundant flight parameter sensors but to the detriment of the aircraft weight and so to the cost and performances. This paper proposes an algorithm using PLS (Partial Least Squares) to estimate a flight parameter from independent sensor measurements. The estimates are then used as so-called “software” or “virtual” sensors, allowing aircraft weight saving. This algorithm is based on an iterative processing and thus can be used in real time in the embedded flight control computer. Furthermore, the resulting flight parameter estimates can be used to detect failures. Different detection strategies are proposed and results show that this method can lead to robust detections.
Authors
Citation
Cazes, F., Mailhes, C., Chabert, M., Goupil, P. et al., "Flight Parameter Estimation for Augmented Flight Control System Autonomy," SAE Technical Paper 2011-01-2801, 2011, https://doi.org/10.4271/2011-01-2801.Also In
References
- Traverse, P. Lacaze, I. Souyris, J. 2004 Airbus Fly-By-Wire: A Total Approach To Dependability Proc. 18 th IFIP World Computer Congress Toulouse, France 191 212
- Favre, C. 1994 Fly-by-wire for commercial aircraft: the Airbus experience International Journal of Control 59 1 139 157
- Goupil, P. 2011 AIRBUS State of the Art and Practices on FDI and FTC in Flight Control System Control Engineering Practice 19 2011 524 539 10.1016/j.conengprac.2010.12.009
- Rosenberg, K. 1998 “FCS architecture definition (issue 1)” Deliverable 3.4, BE97-4098 ADFCS
- Patton, R.J. Frank, P.M. Clark, R.N. 1989 Fault Diagnosis in Dynamic Systems, Theory and Applications New York Prentice-Hall 1989
- Chen, J. Patton, R.J. 1999 Robust model-based fault diagnosis for dynamic systems Kluwer Academic Publishers
- Ding, S.X. 2008 Model-based Fault Diagnosis Techniques. Design Schemes, Algorithms, and Tools Springer Heidelberg, Berlin
- Zolghadri, A. 2002 Early warning and prediction of flight parameter abnormalities for improved system safety assessment Reliability Engineering and System Safety 16 19 27
- Goupil, P. 2010 Oscillatory Failure Case Detection In The A380 Electrical Flight Control System By Analytical Redundancy Control Engineering Practice 18 2010 1110 1119 10.1016/j.conengprac.2009'04.003
- Tenenhaus, Michel 1998 La regression PLS, théorie et pratique 254 10: 2710807351
- Chiang, L.H. Russell, E.L. Braatz, R.D. 2001 Fault Detection and Diagnosis in Industrial Systems Springer 279 1-85233-327-8
- Haykin, Simon 2003 Least-Mean-Square Adaptative Filters (Adaptive and Learning Systems for Signal Processing, Communications and Control Series) Wiley-Interscience 512