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SMAC-FDI: A single model active fault detection and isolation system for unmanned aircraft

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Języki publikacji
EN
Abstrakty
EN
This article presents a single model active fault detection and isolation system (SMAC-FDI) which is designed to efficiently detect and isolate a faulty actuator in a system, such as a small (unmanned) aircraft. This FDI system is based on a single and simple aerodynamic model of an aircraft in order to generate some residuals, as soon as an actuator fault occurs. These residuals are used to trigger an active strategy based on artificial exciting signals that searches within the residuals for the signature of an actuator fault. Fault isolation is carried out through an innovative mechanism that does not use the previous residuals but the actuator control signals directly. In addition, the paper presents a complete parameter-tuning strategy for this FDI system. The novel concepts are backed-up by simulations of a small unmanned aircraft experiencing successive actuator failures. The robustness of the SMAC-FDI method is tested in the presence of model uncertainties, realistic sensor noise and wind gusts. Finally, the paper concludes with a discussion on the computational efficiency of the method and its ability to run on small microcontrollers.
Rocznik
Strony
189--201
Opis fizyczny
Bibliogr. 35 poz., rys., tab., wykr.
Twórcy
  • CNRS, I3S, UMR 7271, University of Nice Sophia Antipolis, 2000 Route des Lucioles, Bat. Euclide B, Les Algorithmes, 06903 Sophia Antipolis, France
Bibliografia
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  • [3] Azam, M., Pattipati, K., Allanach, J., Poll, S. and Petterson-Hine, A. (2005). In-flight fault detection and isolation in aircraft flight control systems, Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA, paper 1429.
  • [4] Bateman, F., Noura, H. and Ouladsine, M. (2011). Active fault diagnosis and major actuator failure accommodation: Application to a UAV, in A. Balint (Ed.), Advances in Flight Control Systems, InTech, Rijeka, pp. 135–158.
  • [5] Belcastro, C. and Chang, B.-C. (2002). Uncertainty modeling for robustness analysis of failure detection and accommodation systems, Proceedings of the IEEE American Control Conference, Anchorage, AK, USA, pp. 4776–4782.
  • [6] Benini, B., Castaldi, P. and Simani, S. (2009). Fault Diagnosis for Aircraft System Models: An Introduction from Fault Detection to Fault Tolerance, VDM Verlag Dr. Muller, Saarbrucken.
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  • [8] Bonfè, M., Castaldi, P., Mimmo, N. and Simani, S. (2011). Active fault tolerant control of nonlinear systems: The cart-pole example, International Journal of Applied Mathematics and Computer Science 21(3): 441–455, DOI: 10.2478/v10006-011-0033-y.
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  • [12] Campbell, S.L. and Nikoukhah, R. (2004). Auxiliary Signal Design for Failure Detection, Princeton University Press, Princeton, NJ.
  • [13] Castaldi, P., Geri, W., Bonfè, M., Simani, S. and Benini, M. (2010). Design of residual generators and adaptive filters for the FDI of aircraft model sensors, Control Engineering Practice 18(5): 449–495, DOI:10.1016/j.conengprac.2008.11.006.
  • [14] Chen, J. and Patton, R.J. (1999). Robust Model-Based Diagnosis for Dynamic Systems, Kluwer Academic, Boston, MA.
  • [15] Ducard, G. (2009). Fault-tolerant Flight Control and Guidance Systems: Practical Methods for Small Unmanned Aerial Vehicles, Advances in Industrial Control, Springer-Verlag, London.
  • [16] Ducard, G. (2013). The SMAC fault detection and isolation scheme: Discussions, improvements, and application to a UAV, Proceedings of the IEEE 2013 Conference on Control and Fault Tolerant Systems (SysTol’13), Nice, France, pp. 480–485.
  • [17] Ducard, G. and Geering, H.P. (2006). A reconfigurable flight control system based on the EMMAE method, Proceedings of the IEEE American Control Conference, Minneapolis, MN, USA, pp. 5499–5504.
  • [18] Ducard, G. and Geering, H.P. (2008). Efficient nonlinear actuator fault detection and isolation system for unmanned aerial vehicles, AIAA Journal of Guidance, Control, and Dynamics 31(1): 225–237.
  • [19] Ducard, G. and Geering, H.P. (2010). SMAC-FDI: New active fault detection and isolation scheme with high computational efficiency, Proceedings of the IEEE 2010 Conference on Control and Fault Tolerant Systems, Nice, France, pp. 30–37.
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  • [28] Möckli, M. (2006). Guidance and Control for Aerobatic Maneuvers of an Unmanned Airplane, Ph.D. thesis, Diss. No. 16586, ETH Zurich, Zurich.
  • [29] Patton, R.J. and Chen, J. (1997). Observer-based fault detection and isolation: Robustness and applications, Control Engineering Practice 5(5): 671–682.
  • [30] Patton, R.J., Uppal, F.J., Simani, S. and Polle, B. (2008). Reliable fault diagnosis scheme for a spacecraft control system, Journal of Risk and Reliability 222(2): 139–152, DOI: 10.1243/1748006XJRR98.
  • [31] Rodrigues, M., Theilliol, D., Aberkane, S. and Sauter, D. (2007). Fault tolerant control design for polytopic LPV systems, International Journal of Applied Mathematics and Computer Science 17(1): 27–37, DOI:10.2478/v10006-007-0004-5.
  • [32] Simani, S., Fantuzzi, C. and Patton, R. (2003). Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques, Advances in Industrial Control, Springer-Verlag, London.
  • [33] Tanaka, N., Suzuki, S., Masui, K. and Tomita, H. (2006). Restructurable guidance and control for aircraft with failures considering gusts effects, AIAA Journal of Guidance, Control, and Dynamics 29(3): 635–642.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0516024e-183e-48c1-b276-e6af3412bff8
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