Actuator Fault Detection in UAVs

  • Guillaume DucardEmail author
Reference work entry


Future unmanned aerial vehicles (UAVs) will be designed to achieve their missions with increased efficiency, safety, and security. To this end, an efficient fault detection and isolation (FDI) system should be capable of monitoring the health status of the aircraft. Fault-tolerant control systems for small and low-cost UAVs should not increase significantly the number of actuators or sensors needed to achieve the safer operation. This chapter is dedicated to actuator fault detection systems for UAVs, with two main requirements: realtime capability and modularity. After defining the terminology employed in this field, this chapter reviews some commonly used techniques in FDI systems. The chapter continues by presenting briefly the mathematical model of a UAV which will serve as a basis for the design of two actuator FDI systems. The first method presents and illustrates the multiple-model approach, whereas the second method presents an FDI system which is based on a single model. Both methods have been enhanced by a mechanism that actively tests actuators in order to efficiently detect and isolate actuator faults and failures. This chapter explains the advantages and drawbacks of each method and discusses issues of robustness against model uncertainties and external perturbation. In addition, aspects of computational load are addressed. Finally, the FDI systems of this chapter are applied to a realistic model of an unmanned aircraft, and the performance of the methods is shown in simulation.


Actuator Fault Fault Probability Turn Rate Fault Isolator Actuator Failure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. R.J. Adams, Robust Multivariable Flight Control (Springer, London/New York, 1994)CrossRefGoogle Scholar
  2. M. Azam, K. Pattipati, J. Allanach, S. Poll, A. Petterson-Hine, In-flight fault detection and isolation in aircraft flight control systems, in Proceedings of IEEE Aerospace Conference, paper 1429, (BigSky, MT, 2005)Google Scholar
  3. F. Bateman, H. Noura, M. Ouladsine, Active fault diagnosis and major actuator failure accommodation: application to a UAV, in Advances in Flight Control Systems, ed. by A. Balint (InTech, Rijeka, 2011), pp. 137–158Google Scholar
  4. C. Belcastro, B.-C. Chang, Uncertainty modeling for robustness analysis of failure detection and accommodation systems, in Proceedings of the IEEE American Control Conference, Anchorage, 2002, pp. 4776–4782Google Scholar
  5. M. Bodson, An adaptive algorithm with information-dependant data forgetting, in Proceedings of the IEEE American Control Conference, Seattle, WA, 1995, pp. 3485–3489Google Scholar
  6. J. Boskovic, R. Mehra, Failure detection, identification and reconfiguration in flight control, in Fault Diagnosis and Fault Tolerance for Mechatronic Systems: Recent Advances, ed. by F. Caccavale, L. Villani. Springer Tracts in Advanced Robotics, vol. 1 (Springer, Berlin/Heidelberg, 2003), pp. 129–167. 10.1007/3–540–45737–2–5CrossRefGoogle Scholar
  7. J.D. Boskovic, S.E. Bergstrom, R.K. Mehra, Robust integrated flight control design under failures, damage, and state-dependant disturbances. AIAA J. Guid. Control Dyn. 28(5), 902–917 (2005)CrossRefGoogle Scholar
  8. J.D. Boskovic, J. Redding, R.K. Mehra, Stable adaptive reconfigurable flight control with self-diagnostics, in Proceedings of the IEEE American Control Conference, New York, 2007, pp. 5765–5770Google Scholar
  9. J. Brinker, K.A. Wise, Flight testing of a reconfigurable flight control law on the X-36 tailless fighter aircraft, in Proceedings of the AIAA Guidance, Navigation, and Control Conference, Denver, CO, 2000Google Scholar
  10. R.G. Brown, P.Y.C. Hwang, Introduction to Random Signals and Applied Kalman Filtering (Wiley, New York, 1997)zbMATHGoogle Scholar
  11. S. Brunke, M. Campbell, Estimation architecture for future autonomous vehicles, in Proceedings of the IEEE American Control Conference, Anchorage, 2002, pp. 1108–1114Google Scholar
  12. J. Buffington, P. Chandler, M. Pachter, On-line identification for aircraft with distributed control effectors. AIAA J. Guid. Control Dyn. 9, 1033–1049 (1999)Google Scholar
  13. A.J. Calise, S. Lee, M. Sharma, Direct adaptive reconfigurable control of a tailless fighter aircraft, in Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Boston, MA, 1998Google Scholar
  14. M.E. Campbell, J.W. Lee, E. Scholte, D. RathBun, Simulation and flight test of autonomous aircraft estimation, planning, and control algorithms. AIAA J. Guid. Control Dyn. 30(6), 1597–1609 (2007)CrossRefGoogle Scholar
  15. J. Chen, R.J. Patton, Robust Model Based Diagnosis for Dynamic Systems (Kluwer, Dordrecht, 1999)CrossRefzbMATHGoogle Scholar
  16. J. Chen, R.J. Patton, H. Zhang, Design of unknown input observers and robust fault detection filters. Int. J. Control 63(1), 85–105 (1996)CrossRefzbMATHMathSciNetGoogle Scholar
  17. E.Y. Chow, A.S. Willsky, Analytical redundancy and the design of robust detection systems. IEEE Trans. Autom. Control 29(7), 603–614 (1984)CrossRefzbMATHMathSciNetGoogle Scholar
  18. E.G. Collins, T. Song, Robust H estimation and fault detection of uncertain dynamic systems. AIAA J. Guid. Control Dyn. 23(5), 857–864 (2000)CrossRefGoogle Scholar
  19. G.J.J. Ducard, Fault-Tolerant Flight Control and Guidance Systems for a Small Unmanned Aerial V e h i c l e. Ph.D. thesis, ETH Zürich, 2007 Diss. No. 17505Google Scholar
  20. G. Ducard,. Fault-Tolerant Flight Control and Guidance Systems: Practical Methods for Small Unmanned Aerial Vehicles (Springer, London, 2009). ISBN:978–1–84882–560–4Google Scholar
  21. G. Ducard, H.P. Geering, A reconfigurable flight control system based on the EMMAE method, in Proceedings of the IEEE American Control Conference, Minneapolis, MN, 2006, pp. 5499–5504Google Scholar
  22. G. Ducard, H.P. Geering, Efficient nonlinear actuator fault detection and isolation system for unmanned aerial vehicles. AIAA J. Guid. Control Dyn. 31(1), 225–237 (2008)CrossRefGoogle Scholar
  23. G. Ducard, H.P. Geering, SMAC-FDI: new active fault detection and isolation scheme with high computational efficiency, in Proceedings of the IEEE 2010 Conference on Control and Fault Tolerant Systems, Nice, France, 2010, pp. 30–37CrossRefGoogle Scholar
  24. P. Eide, P.S. Maybeck, An MMAE failure detection system for the F-16. IEEE Trans. Aerosp. Electron. Syst. 32(3), 1125–1136 (1996)CrossRefGoogle Scholar
  25. M. Elgersma, S. Glavaski, Reconfigurable control for active management of aircraft system failures, in Proceedings of IEEE American Control Conference, Arlington, VA, 2001, pp. 2627–2639Google Scholar
  26. M. Elgersma, D. Enns, S. Shald, P. Voulgaris, Parameter identification for systems with redundant actuators, in Proceedings of the AIAA Guidance, Navigation and Control Conference and Exhibit, Boston, MA, 1998Google Scholar
  27. S. Fekri, M. Athans, A. Pascoal, Issues, progress and new results in robust adaptive control. Int. J. Adapt. Control Signal Process. 20(10), 519–579 (2006)CrossRefzbMATHMathSciNetGoogle Scholar
  28. P. Frank, Enhancement of robustness in observer-based fault detection. Int. J. Control 59(4), 955–984 (1994)CrossRefzbMATHGoogle Scholar
  29. J.J. Gertler, Fault detection and isolation using parity relations. Control Eng. Pract. 5(5), 653–661 (1997)CrossRefGoogle Scholar
  30. C. Hajiyev, F. Caliskan, Fault-Diagnosis and Reconfiguration in Flight Control Systems (Kluwer Academic Publishers, Dordrecht, 2003). ISBN:978–1–4020–7605–3Google Scholar
  31. R. Isermann, Fault-Diagnosis Systems, An Introduction from Fault Detection to Fault Tolerance (Springer, Berlin/Heidelberg, 2006)Google Scholar
  32. S. Julier, J. Uhlmann, H.F. Durrant-Whyte, A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE Trans. Autom. Control 45(3), 477–482 (2000)CrossRefzbMATHMathSciNetGoogle Scholar
  33. R.E. Kalman, A new approach to linear filtering and prediction problems. J. Basic Eng. 82(1), 35–46 (1960)CrossRefGoogle Scholar
  34. B.H. Koh, Z. Li, P. Dharap, S. Nagarajaiah, M.Q. Phan, Actuator failure detection through interaction matrix formulation. AIAA J. Guid. Control Dyn. 28(5), 895–901 (2005)CrossRefGoogle Scholar
  35. D.T. Magill, Optimal adaptive estimation of sampled stochastic processes. IEEE Trans. Autom. Control 10(4), 434–439 (1965)CrossRefMathSciNetGoogle Scholar
  36. A. Marcos, S. Ganguli, G.J. Balas, An application of H fault detection and isolation to a transport aircraft. Control Eng. Pract. 13, 105–119 (2005)CrossRefGoogle Scholar
  37. P.S. Maybeck, (1994). Stochastic Models, Estimation, and Control, Volume 1 (Academic, New York, Inc, 1979); republished by Navtech, Arlington, VA, 1994Google Scholar
  38. P.S. Maybeck, Multiple model adaptive algorithms for detecting and compensating sensor and actuator/surface failures in aircraft flight control systems. Int. J. Robust Nonlinear Control 9(14), 1051–1070 (1999)CrossRefGoogle Scholar
  39. P.S. Maybeck, R.D. Stevens, Reconfigurable flight control via multiple model adaptive control methods. IEEE Trans. Aerosp. Electron. Syst. 27(3), 470–479 (1991)CrossRefGoogle Scholar
  40. M. Möckli, Guidance and Control for Aerobatic Maneuvers of an Unmanned Airplane. Ph.D. thesis, ETH Zurich, 2006. Diss No. 16586Google Scholar
  41. L. Ni, Fault-Tolerant Control of Unmanned Underwater Vehicles. Ph.D. thesis, VA Tech. Univ., Blacksburg, VA, 2001Google Scholar
  42. R.J. Patton, J. Chen, Observer-based fault detection and isolation: robustness and applications. Control Eng. Pract. 5(5), 671–682 (1997)CrossRefGoogle Scholar
  43. R.J. Patton, P.M. Frank, R.N. Clark, Fault Diagnosis in Dynamic Systems: Theory and Applications (Prentice-Hall, Englewood Cliffs, 1989)Google Scholar
  44. R.J. Patton, P.M. Frank, R.N. Clark, Issues of Fault Diagnosis for Dynamic Systems (Springer, London, 2000)CrossRefGoogle Scholar
  45. R.J. Patton, F.J. Uppal, S. Simani, B. Polle, Reliable fault diagnosis scheme for a spacecraft control system. J. Risk Reliab. 222, 139–152 (2008). doi:10.1243/1748006XJRR98Google Scholar
  46. L. Perea, P. Elosegui, New state update equation for the unscented Kalman filter. AIAA J. Guid. Control Dyn. 31(5), 1500–1504 (2008)CrossRefGoogle Scholar
  47. I. Rapoport, Y. Oshman, Fault-tolerant particle filtering by using interacting multiple model-based Rao-Blackwellisation. AIAA J. Guid. Control Dyn. 28(6), 1171–1177 (2005)CrossRefGoogle Scholar
  48. H.P. Rotstein, R. Ingvalson, T. Keviczky, G.J. Balas, Fault-detection design for uninhabited aerial vehicles. AIAA J. Guid. Control Dyn. 29(5), 1051–1060 (2006)CrossRefGoogle Scholar
  49. D. Rupp, G. Ducard, H.P. Geering, E. Shafai, Extended multiple model adaptive estimation for the detection of sensor and actuator faults, in Proceedings of IEEE Control and Decision Conference, and European Control Conference, Seville, Spain, 2005, pp. 3079–3084CrossRefGoogle Scholar
  50. P.A. Samara, G.N. Fouskitakis, J.S. Sakellariou, S.D. Fassois, A statistical method for the detection f sensor abrupt faults in aircraft control systems. IEEE Trans. Control Syst. Technol. 16(4), 789–798 (2008)CrossRefGoogle Scholar
  51. J.D. Schierman, D.G. Ward, J.R. Hull, N. Gandhi, M.W. Oppenheimer, D.B. Doman, Integrated adaptive guidance and control for re-entry vehicles with flight-test results. AIAA J. Guid. Control Dyn. 27(6), 975–988 (2004)CrossRefGoogle Scholar
  52. J.-Y. Shin, C. Belcastro, T. Khong, Closed-loop evaluation of an integrated failure identification and fault tolerant control system for a transport aircraft, in AIAA Guidance, Navigation, and Control Conference and Exhibit, Keystone, CO, 2006. AIAA 2006–6310Google Scholar
  53. Control Conference and Exhibit, Keystone, CO, 2006. AIAA 2006–6310 D. Shore, M. Bodson, Flight testing of a reconfigurable control system on an unmanned aircraft. AIAA J. Guid. Control Dyn. 28(4), 698–707 (2005)CrossRefGoogle Scholar
  54. AIAA J. Guid. Control Dyn. 28(4), 698–707 (2005) R.F. Stengel, Flight Dynamics (Princeton University Press, Princeton, 2004)Google Scholar
  55. B. Stevens, F. Lewis, Aircraft Control and Simulation, 2nd edn. (Wiley, New York, 2003)Google Scholar
  56. I. Szaszi, A. Marcos, G. Balas, J. Bokor, Linear Parameter-varying detection filter design for a Boeing 747-100/200 aircraft. AIAA J. Guid. Control Dyn. 28(3), 461–470 (2005)CrossRefGoogle Scholar
  57. Boeing 747-100/200 aircraft. AIAA J. Guid. Control Dyn. 28(3), 461–470 (2005) N. Tanaka, S. Suzuki, K. Masui, H. Tomita, Restructurable guidance and control for aircraft with failures considering gusts effects. AIAA J. Guid. Control Dyn. 29(3), 635–642 (2006)CrossRefGoogle Scholar
  58. G. Tao, S. Chen, X. Tang, S.M. Joshi, Adaptive Control of Systems with Actuator Failures (Springer, London/Berlin/Heidelberg, 2004)CrossRefzbMATHGoogle Scholar
  59. J. Urnes, R. Yeager, J. Stewart, Flight demonstration of the self-repairing flight control system in a NASA F-15 aircraft, in National Aerospace Electronics Conference, Rept. 90CH2881–1, Dayton, OH, 1990Google Scholar
  60. D. Ward, R. Barron, A self-designing receding horizon optimal flight controller, in Proceedings of the IEEE American Control Conference, Seattle, WA, 1995, pp. 3490–3494Google Scholar
  61. D. Ward, R.L. Barron, M.P. Carley, T.J. Curtis, Real-time Parameter identification for self-designing flight control, in Proceedings of the National Aerospace and Electronics Conference (NAECON), Dayton, OH, 1994Google Scholar
  62. D.G. Ward, J.F. Monaco, M. Bodson, Development and flight testing of a Parameter identification algorithm for reconfigurable control. AIAA J. Guid. Control Dyn. 21(6), 948–956 (1998)CrossRefGoogle Scholar
  63. K. Wise, J. Brinker, A. Calise, D. Enns, M. Elgersma, P. Voulgaris, Direct adaptive reconfigurable flight control for a tailless advanced fighter aircraft. Int. J. Robust Nonlinear Control 9, 999–1012 (1999)CrossRefGoogle Scholar
  64. A. Younghwan, A Design of Fault Tolerant Flight Control Systems for Sensor and Actuator Failures Using On-Line Learning Neural Networks. Ph.D. thesis, West Virginia University, 1998Google Scholar
  65. P. Zarchan, H. Musoff, Fundamentals of Kalman Filtering: A Practical Approach. Progress in Astronautics and Aeronautics, vol. 208, 2nd edn. (AIAA Inc., Reston, 2005)Google Scholar
  66. Y. Zhang, J. Jiang, Integrated design of reconfigurable fault-tolerant control systems. AIAA J. Guid. Control Dyn. 24(1), 133–136 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.I3S CNRS-UNS, Sophia AntipolisFrance ETH Zurich, IDSCZurichSwitzerland

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