A comparative study of NN- and EKF-based SFDA schemes with application to a nonlinear UAV model

International Journal of Control

Volumn 83, Issue 5, 2010, Pages 1025-1043

  Samy, Ihab ^a   Postlethwaite, Ian ^a   Gu, Da Wei ^a  

^a UNIVERSITY OF LEICESTER   (United Kingdom)

Author keywords

Extended Kalman filter; Neural networks; Residual generator; Sensor validation

Indexed keywords

BAE SYSTEMS; COMPARATIVE STUDIES; ESTIMATION ERRORS; EXECUTION TIME; FALSE ALARM RATE; FALSE ALARMS; FAULT TYPES; ME-XICO; RESIDUAL GENERATOR; SENSOR FAULT DETECTION; SENSOR REDUNDANCY; SENSOR VALIDATION; TEST CONDITION; UNMANNED AIR VEHICLES;

ERRORS; EXTENDED KALMAN FILTERS; FAULT DETECTION; POSITION CONTROL; REMOTELY OPERATED VEHICLES; SENSORS; UNMANNED AERIAL VEHICLES (UAV);

NEURAL NETWORKS;

EID: 77951557860     PISSN: 00207179     EISSN: 13665820     Source Type: Journal    
DOI: 10.1080/00207170903552059     Document Type: Article

References (35)

1. Alessandri, A., Caccia, M., and Veruggio, G. (1999), 'Fault Detection of Actuator Faults in Unmanned Underwater Vehicle', Control Engineering Practice, 7, 357-368. (Pubitemid 29368665)
2. An, Y. (1998), 'A Design of Fault Tolerant Flight Control Systems for Sensor and Actuator Failures Using On-line Learning Neural Networks', PhD thesis, Department of Mechanics and Aerospace Engineering, Morgantown, West Virginia.
3. Buonanno, A., and Cook, M. V. (2005), 'An Aerodynamic Simulation Model of the Eclipse UAV', Internal Report No. FLAV-A01-002, Cranfield University, Bedford, UK.
4. Campa, G., Fravolini, M. L., Napolitano, M., and Seanor, B. (2002), 'Neural Networks Sensor Validation for the Flight Control System of a B777 Research Model', American Control Conference, 1, 412-417.
5. Capriglione, D., Liguori, C., and Pietrosanto, A. (2007), 'Real Time Implementation of IDFIA Scheme in Automotive Systems', IEEE Transactions on Instrumentation and Measurement, 56, 824-830. (Pubitemid 46784551)
6. Chiang, C. Y., Juang, J. C. and Youssef, H. (1994), 'Neural Network Approach to Aircraft Fault Detection, Isolation and Estimation Design', AIAA-1994-273, AIAA 32nd Aerospace Sciences Meeting and Exhibit, Reno, NV, USA, 10-13 January 1994.
7. Clark, R. N., and Setzer, W. (1980), 'Sensor Fault Detection in a System with Random Disturbances', IEEE Transactions on Aerospace and Electronic Systems, 16, 468-473. (Pubitemid 11429314)
8. Cybenko, G. (1989), 'Approximation by Superposition of Sigmoidal functions', Mathematics of Control, Signals, and Systems, 2, 303-309.
9. Gallinari, F. (1998), Industrial Applications of Neural Networks, Great Britain: World Scientific Publishing Co. Pte. Ltd..
10. Haykin, S. (1994), Neural Networks: A Comprehensive Foundation, New York: Macmillan College Publishing Company.
11. Heredia, G., Ollero, A., Mahtani, R., Remub, V., and Mausial, M. (2005), 'Detection of Sensor Faults in Autonomous Helicopters', in Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, Spain, pp. 2229-2234. (Pubitemid 46084119)
12. Hornik, K., Stinchcombe, M., and White, H. (1989), 'Multilayer Feedforward Networks are Universal Approximators', Neural Networks, 2, 359-366. (Pubitemid 20609008)
13. Huang, W., Wang, K., and Chen, Q. (1996), 'Sensor Failure Detection and Data Recovery Based on Neural Network', AIAA-1996-2932, AIAA, ASME, SAE and ASEE, 32nd Joint Propulsion Conference and Exhibit, Lake Buena Vista, FL, USA, 1-3 July 1996.
14. Isermann, R. (1984), 'Process Fault Detection Based on Modelling and Estimation Methods: A survey', Automatica, 20, 387-404. (Pubitemid 14664634)
15. Isermann, R., and Balle, P. (1997), 'Trends in the Application of Model-based Fault Detection and Diagnosis of Technical Processes', Control Engineering Practice, 5, 709-719. (Pubitemid 27414363)
16. Kadirkamanathan, V., and Niranjan, M. (1993), 'A Function Estimation Approach to Sequential Learning with Neural Networks', Neural Computatation, 5, 954-975.
17. Kalman, R. E. (1960), 'A New Approach to Linear Filtering and Prediction Problems', Journal of Basic Engineering, 82, 35-45.
18. Li, Y., Sundararajan, N., and Saratchandran, P. (2000), 'Analysis of Minimal Radial Basis Function Network Algorithm for Real Time Identification of Nonlinear Dynamic Systems', IEEE Control Theory and Application, 4, 476-484.
19. Mattern, D., Jaw, L., Guo, T. H., Graham, R., and McCoy, W. (1998), 'Using Neural Networks for Sensor Validation', AIAA-1998-3547.
20. Mehra, R. K., and Peschon, J. (1971), 'An Innovative Approach to Fault Detection and Diagnosis in Dynamic Systems', Automatica, 7, 637-643.
21. Moller, J., Litt, J., and Guo, T. H. (1998), 'Neural Network Based Sensor Validation for Turboshaft Engines', AIAA-1998-3605, AIAA, ASME, SAE and ASEE, 34th Joint Propulsion Conference and Exhibit, Cleverland, OH, USA, 13-15 July 1998.
22. Motyka, P., Bonnice, W., Hall, S., and Wagner, E. (1985), 'The Evaluation of Failure Detection and Isolation Algorithms for Restructurable Control', NASA Contractor Report No. 177983.
23. Napolitano, M., Neppach, C., Casdorph, V., and Innocenti, M. (1994), 'Sensor Failure Detection, Identification and Accommodation Using Online Learning Neural Architectures', AIAA Report No. AIAA-1994-3598, AIAA Guidance, Navigation and Control Conference, Scottsdale, AZ, USA, 1-3 August 1994.
24. Napolitano, M., Neppach, C., Casdorph, V., and Innocenti, M. (1995), 'Neural Network Based Scheme for Sensor Failure Detection, Identification and Accommodation', AIAA Journal of Guidance Control and Dynamics, 18, 1280-1286.
25. Napolitano, M., An, Y., and Seanor, B. (2000), 'A Fault Tolerant Flight Control System for Sensor and Actuator Failures Using Neural Networks', Aircraft Design, 3, 103-128.
26. Napolitano, N., An, Y., Seanor, B., Pispistos, S., and Martinelli, D. (1999), 'Application of a Neural Sensor Validation Scheme to Actual Boeing B737 Flight Data', in Proceedings of the AIAA Guidance Navigation and Control Conference, pp. 139-147.
27. Napolitano, M., Windon, D., Casanova, J., and Innocenti, M. (1996), 'A Comparison Between Kalman Filter and Neural Network Approaches for Sensor Validation', AIAA Report No. AIAA-1996-3894, AIAA Guidance, Navigation and Control Conference, San Diego, CA, USA, 29-31 July 1996.
28. Neppach, C., and Casdorph, V. (1995), 'Sensor Failure Detection, Identification and Accommodation in a System Without Sensor Redundancy', AIAA Report No. AIAA-1995-11, AIAA 33rd Aerospace Sciences Meeting and Exhibit, Reno, NV, 9-12 January 1995.
29. Perla, R., Mukhopadhyay, S., and Samanta, A. (2004), 'Sensor Fault Detection and Isolation Using Artificial Neural Networks', IEEE Region Conference TENCON, 4, 676-679. (Pubitemid 41676146)
30. Powell, M. J. D. (1987), 'Radial Basis Function for Multivariable Interpolation: A Review', in Algorithms for Approximation, eds. J. C. Mason and M. G. Cox, Oxford, UK: Clarendon Press, pp. 143-167.
31. Samy, I., Postlethwaite, I., and Gu, D.-W. (2008a), 'Neural Network Sensor Validation Scheme Demonstrated on a UAV Model', in IEEE Proceedings of CDC, Cancun, Mexico, pp. 1237-1242.
32. Samy, I., Postlethwaite, I., and Gu, D.-W. (2008b), 'Detection of Additive Sensor Faults in a UAV Model Using Neural Networks', in Proceedings of UKACC, UK, Manchester, p. Tu.05.05.
33. Sheng, W., Giampiero, C., Napolitano, M., and Fravolini, M. (2002), 'Online Learning RBF Neural Networks for Sensor Validation', AIAA Report No. AIAA-2002-4996, 2002, AIAA Guidance, Navigation and Control Conference and Exhibit, Monterey, CA, USA, 5-8 August 2002.
34. Sorenson, H. W. (1985), Kalman Filtering: Theory and Application, New York: IEEE Press.
35. Trammel, C., Vossler, G., and Feldmann, M. (1997), 'UK Ministry of Defence Generic Health and Usage Monitoring System (GenHUMS) ', Journal of Aircraft Engineering and Aerospace Technology, 69, 414-422.