Skip to main content

Advertisement

Log in

Diagnosis of Icing and Actuator Faults in UAVs Using LPV Unknown Input Observers

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions. The developed theory is supported by simulations illustrating the diagnosis of actuator faults and icing in a small UAV. The obtained results validate the effectiveness of the proposed approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Zhang, Y., Jiang, J.: Bibliographical review on reconfigurable fault-tolerant control systems. Annu. Rev. Control. 32, 229–252 (2008)

    Article  Google Scholar 

  2. Gao, Z., Cecati, C., Ding, S.X.: A survey of fault diagnosis and fault-tolerant techniques—Part I: fault diagnosis with model-based and signal-based approaches. IEEE Trans. Ind. Electron. 62(6), 3757–3767 (2015)

    Article  Google Scholar 

  3. De Persis, C., Isidori, A.: A geometric approach to nonlinear fault detection and isolation. IEEE Trans. Autom. Control 46(6), 863–865 (2001)

    MathSciNet  MATH  Google Scholar 

  4. Kaboré, P., Wang, H.: Design of fault diagnosis filters and fault-tolerant control for a class of nonlinear systems. IEEE Trans. Autom. Control 46(11), 1805–1810 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  5. López-Estrada, F.R., Ponsart, J.C., Theilliol, D., Zhang, Y., Astorga-Zaragoza, C.M.: LPV Model-based tracking control and robust sensor fault diagnosis for a quadrotor UAV. J. Intell. Robot. Syst. 84(1), 163–177 (2016)

    Article  Google Scholar 

  6. Caliskan, F., Hajijev, C.: A review of in-flight detection and identification of aircraft icing and reconfigurable control. Prog. Aerosp. Sci. 60, 12–34 (2013)

    Article  Google Scholar 

  7. Gent, R., Dart, N., Cansdale, J.: Aircraft icing. Phil. Trans. R. Soc. Lond. Ser. A: Math. Phys. Eng. Sci. 358, 2873–2911 (2000)

    Article  MATH  Google Scholar 

  8. Lampton, A., Valasek, J.: Prediction of icing effects on the dynamic response of light airplanes. J. Guid. Control. Dyn. 30(3), 722–732 (2007)

    Article  Google Scholar 

  9. Rutherford, R., Dudman, R.: Zoned aircraft de-icing system and method,, U.S. Patent 6237874, filed 15 Oct. 1999. Available: http://www.google.com/patents/US6237874

  10. Sørensen, K.L., Helland, A.S., Johansen, T.A.: Carbon nanomaterial-based wing temperature control system for in-flight anti-icing and de-icing of unmanned aerial vehicles. In: IEEE Aerospace Conference (2015)

  11. Sørensen, K.L., Johansen, T.A.: Thermodynamics of a carbon nano-materials based icing protection system for unmanned aerial vehicle. In: IEEE Aerospace Conference (2016)

  12. Hajiyev, C., Caliskan, F.: Fault Diagnosis and Reconfiguration in Flight Control Systems. Springer Science and Business Media, Berlin (2003)

    Book  MATH  Google Scholar 

  13. Tousi, M., Khorasani, K.: Robust observer-based fault diagnosis for an unmanned aerial vehicle. In: Proceedings of the IEEE International Systems Conference (SysCon), pp. 428–434 (2011)

  14. Sørensen, K.L., Blanke, M., Johansen, T.A.: Diagnosis of wing icing through lift and drag coefficient change detection for small unmanned aircraft. In: Proceedings of the 9th IFAC Symposium on Fault Detection Supervision and Safety of Technical Processes (2015)

  15. Lee, H., Snyder, S., Hovakimyan, N.: An Adaptive unknown input observer for fault detection and isolation of aircraft actuator faults. In: AIAA Guidance, Navigation, and Control Conference (2014)

  16. Hammouri, H., Tmar, Z.: Unknown input observer for state affine systems: a necessary and sufficient condition. Automatica 46, 271–278 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  17. Basile, G., Marro, G.: On the observability of linear, time-invariant systems with unknown inputs. J. Optim. Theory Appl. 3, 410–415 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  18. Guidorzi, R., Marro, G.: On Wonham stabilizability condition in the synthesis of observers for unknown-input systems. IEEE Trans. Autom. Control 16(5), 499–500 (1971)

    Article  Google Scholar 

  19. Bhattacharyya, S.P.: Observer design for linear systems with unknown inputs. IEEE Trans. Autom. Control 23, 483–484 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  20. Hou, M., Muller, P.C.: Design of observers for linear systems with unknown inputs. IEEE Trans. Autom. Control 37, 871–875 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  21. Chen, J., Patton, R.J., Zhang, H.Y.: Design of unknown input observers and robust fault-detection filters. Int. J. Control. 63(1), 85–105 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  22. Cristofaro, A., Johansen, T.A.: Fault tolerant control allocation using unknown input observers. Automatica 50, 1891–1897 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  23. Cristofaro, A., Johansen, T.A.: An unknown input observer approach to icing detection for unmanned aerial vehicles with linearized longitudinal motion. In: Proceedings of the American Control Conference (ACC), pp. 207–213 (2015)

  24. Cristofaro, A., Johansen, T.A., Aguiar, A.P.: Icing detection and identification for unmanned aerial vehicles: multiple model adaptive estimation. In: Proceedings of the European Control Conference (ECC), pp. 1645–1650 (2015)

  25. Rotondo, D., Cristofaro, A., Johansen, T.A., Nejjari, F., Puig, V.: Icing detection in unmanned aerial vehicles with longitudinal motion. In: Proceedings of the IEEE Multi-conference on Systems and Control (MSC), pp. 984–989 (2015)

  26. Seron, M.M., Johansen, T.A., De Doná, J.A., Cristofaro, A.: Detection and estimation of icing in unmanned aerial vehicles using a bank of unknown input observers. In: Proceedings of the Australian Control Conference (AuCC), pp. 87–92 (2015)

  27. Hoffmann, C., Werner, H.: A survey of linear parameter-varying control applications valiyeard by experiments or high-fidelity simulations. IEEE Trans. Control Syst. Technol. 23(2), 416–433 (2015)

    Article  Google Scholar 

  28. Yu, Z., Chen, H., Woo, P.Y.: Gain scheduled output feedback control based on LTI controller interpolation that preserves LPV \(\mathcal {H}_{\infty }\) performance. J. Intell. Robot. Syst. 40(2), 183–206 (2004)

    Article  Google Scholar 

  29. Shamma, J., Athans, M.: Guaranteed properties of gain scheduled control for linear parameter-varying plants. Automatica 27(3), 559–564 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  30. Shamma, J.: An overview of LPV Systems. In: Mohammadpour, J., Scherer, C. (eds.) Control of Linear Parameter Varying Systems with Applications. Springer, Berlin (2012)

  31. Balas, G.: Linear parameter-varying control and its application to a turbofan engine. Int. J. Robust Nonlinear Control 12, 763–796 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  32. Beard, R.W., McLain, T.W.: Small Unmanned Aircraft: Theory and Practice. Princeton University Press, Princeton (2012)

    Book  Google Scholar 

  33. Kwiatkowski, A., Boll, M.-T., Werner, H.: Automated generation and assessment of affine LPV models. In: Proceedings of the 45th IEEE Conference on Decision and Control (CDC), pp. 6690–6695 (2006)

  34. Rotondo, D., Puig, V., Nejjari, F., Witczak, M.: Automated generation and comparison of Takagi-Sugeno and polytopic quasi-LPV models. Fuzzy Set. Syst. 277, 44–64 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  35. Hoblit, F.M.: Gust Loads on Aircraft: Concept and Applications. American Institute of Aeronautics and Astronautics, Washington (1988)

    Book  Google Scholar 

  36. Johansen, T.A., Cristofaro, A., Srensen, K.L., Hansen, J.M., Fossen, T.I.: On estimation of wind velocity, angle-of-attack and sideslip angle of small UAVs using standard sensors. In: Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS) (2015)

  37. Bragg, M.B., Hutchinson, T., Merret, J., Oltman, R., Pokhariyal, D.: Effect of ice accretion on aircraft flight dynamics. In: Proceedings of the 38th AIAA Aerospace Science Meeting and Exhibit (2000)

  38. MacDonald, S.A.F.: From the Ground Up. Aviation Publishers Company Limited, Ottawa (2000)

    Google Scholar 

  39. Hansen, S., Blanke, M.: Diagnosis of airspeed measurement faults for unmanned aerial vehicles. IEEE Trans. Aerosp. Electron. Syst. 50(1), 224–239 (2014)

    Article  Google Scholar 

  40. Toth, R., Henberger, P.S.C., Van Den Hof, P.M.J.: Discretisation of linear parameter-varying state space representations. IET Control Theory Appl. 4(10), 2082–2096 (2010)

    Article  MathSciNet  Google Scholar 

  41. Witczak, M., Pretki, P.: Design of an extended unknown input observer with stochastic robustness techniques and evolutionary algorithms. Int. J. Control. 80(5), 749–762 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  42. Marrison, C.I., Stengel, R.F.: Robust control system design using random search and genetic algorithms. IEEE Trans. Autom. Control 42, 835–839 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  43. Doucet, A., de Freitas, N., Gordon, N.: Sequential Monte Carlo Methods in Practice. Springer, London (2001)

    Book  MATH  Google Scholar 

Download references

Acknowledgements

This work has been supported by the Research Council of Norway through the Centres of Excellence funding scheme (ref. 223254 - AMOS). Damiano Rotondo is also supported by the ERCIM Alain Bensoussan Fellowship programme. This work has also been partially funded by the Spanish Government (MINECO) and FEDER through the project CICYT HARCRICS (ref. DPI2014-58104-R).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Damiano Rotondo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rotondo, D., Cristofaro, A., Johansen, T.A. et al. Diagnosis of Icing and Actuator Faults in UAVs Using LPV Unknown Input Observers. J Intell Robot Syst 91, 651–665 (2018). https://doi.org/10.1007/s10846-017-0716-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-017-0716-1

Keywords

Navigation

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy