Enhanced detection and isolation of angle of attack sensor faults

An enhanced detection and isolation method to monitor the state-of-practice triplex redundant angle of attack measurements on modern civil transport aircraft is presented. The developed fault detection and diagnosis architecture relies on advanced model and signal based techniques monitoring each of the three sensors individually. This allows the correct isolation of erroneous sensors also in case of multiple sensor faults. The gathered isolation information is used in an advanced sensor fusion scheme, allowing the propagation of an adequate angle of attack value to the flight control computer in case of failure. The fault detection and diagnosis system is validated using a high �delity benchmark model of a large commercial transport aircraft using different wind excitations together with challenging pilot and auto-pilot scenarios.

[1]  Halim Alwi,et al.  Development and application of sliding mode LPV fault reconstruction schemes for the ADDSAFE Benchmark , 2014 .

[2]  Andreas Varga On computing achievable fault signatures , 2009 .

[3]  Stéphane Ploix,et al.  Fault diagnosis and fault tolerant control , 2007 .

[4]  A. Varga On computing nullspace bases { a fault detection perspective , 2008 .

[5]  Andres Marcos,et al.  AIRBUS efforts towards advanced real-time Fault Diagnosis and Fault Tolerant Control , 2014 .

[6]  Hans-Dieter Joos Application of Optimization-Based Worst Case Analysis to Control Law Assessment in Aerospace , 2015 .

[7]  Petre Stoica,et al.  Introduction to spectral analysis , 1997 .

[8]  A. Varga Numerically reliable methods for optimal design of fault detection filters , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[9]  Eugene A. Morelli,et al.  Real-Time Parameter Estimation in the Frequency Domain , 1999 .

[10]  Andreas Varga On designing least order residual generators for fault detection and isolation , 2007 .

[11]  Cédric Seren,et al.  Model–Based Techniques for Virtual Sensing of Longitudinal Flight Parameters , 2015, Int. J. Appl. Math. Comput. Sci..

[12]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[13]  Daniel Ossmann,et al.  LPV model-based robust diagnosis of flight actuator faults , 2014 .

[14]  Hans-Dieter Joos,et al.  A Fault Diagnosis Based Reconfigurable Longitudinal Control System for Managing Loss of Air Data Sensors for a Civil Aircraft , 2014 .

[15]  Daniel Ossmann Optimization based tuning of fault detection and diagnosis systems for safety critical systems , 2014 .

[16]  M. Nyberg Criterions for detectability and strong detectability of faults in linear systems , 2000 .

[17]  A. Varga A Fault Detection Toolbox for MATLAB , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.

[18]  Reza Langari,et al.  Sensor Fault Detection And Isolation System , 2014 .

[19]  Jérôme Cieslak,et al.  Fault detection and isolation of aircraft air data/inertial system , 2011 .