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Active fault-tolerant tracking control of a quadrotor with model uncertainties and actuator faults

  • Yu-jiang Zhong
  • Zhi-xiang Liu
  • You-min ZhangEmail author
  • Wei Zhang
  • Jun-yi Zuo
Article

Abstract

This paper presents a reliable active fault-tolerant tracking control system (AFTTCS) for actuator faults in a quadrotor unmanned aerial vehicle (QUAV). The proposed AFTTCS is designed based on a well-known model reference adaptive control (MRAC) framework that guarantees the global asymptotic stability of a QUAV system. To mitigate the negative impacts of model uncertainties and enhance system robustness, a radial basis function neural network is incorporated into the MRAC scheme for adaptively identifying the model uncertainties online and modifying the reference model. Meanwhile, actuator dynamics are considered to avoid undesirable performance degradation. Furthermore, a fault detection and diagnosis estimator is constructed to diagnose lossof- control-effectiveness faults in actuators. Based on the fault information, a fault compensation term is added to the control law to compensate for the adverse effects of actuator faults. Simulation results show that the proposed AFTTCS enables the QUAV to track the desired reference commands in the absence/presence of actuator faults with satisfactory performance.

Key words

Model reference adaptive control Neural network Quadrotor Fault-tolerant control Fault detection and diagnosis 

CLC number

TP273 

References

  1. Avram RC, Zhang XD, Muse J, 2018. Nonlinear adaptive fault-tolerant quadrotor altitude and attitude tracking with multiple actuator faults. Trans Contr Syst Technol, 26(2):701–707. https://doi.org/10.1109/TCST.2017.2670522CrossRefGoogle Scholar
  2. Chen FY, Zhang KK, Wang Z, et al., 2015. Trajectory tracking of a quadrotor with unknown parameters and its fault-tolerant control via sliding mode fault observer. Proc Inst Mech Eng Part I J Syst Contr Eng, 229(4):279–292. https://doi.org/10.1177/0959651814566040Google Scholar
  3. Chen FY, Jiang RQ, Zhang KK, et al., 2016. Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV. IEEE Trans Ind Electron, 63(8):5044–5056. https://doi.org/10.1109/TIE.2016.2552151CrossRefGoogle Scholar
  4. Cheng E, 2015. Aerial photography and videography using drones. In: Johnson K (Ed.), Aerial Photograph Techniques. Peachpit Press, San Francisco.Google Scholar
  5. Dydek ZT, Annaswamy AM, Lavretsky E, 2013. Adaptive control of quadrotor UAVs: a design trade study with flight evaluations. IEEE Trans Contr Syst Technol, 21(4):1400–1406. https://doi.org/10.1109/TCST.2012.2200104CrossRefGoogle Scholar
  6. Hao W, Xian B, 2017. Nonlinear adaptive fault-tolerant control for a quadrotor UAV based on immersion and invariance methodology. Nonl Dynam, 90(4):2813–2826. https://doi.org/10.1007/s11071-017-3842-1MathSciNetCrossRefzbMATHGoogle Scholar
  7. Ioannou PA, Sun J, 1996. Robust Adaptive Control. Prentice-Hall, Upper Saddle River, NJ, USA.zbMATHGoogle Scholar
  8. Joshi SM, Patre P, Tao G, 2012. Adaptive control of systems with actuator failures using an adaptive reference model. J Guid Contr Dynam, 35(3):938–949. https://doi.org/10.2514/1.54332CrossRefGoogle Scholar
  9. Kayacan E, Maslim R, 2017. Type-2 fuzzy logic trajectory tracking control of quadrotor VTOL aircraft with elliptic membership functions. IEEE/ASME Trans Mech, 22(1):339–348. https://doi.org/10.1109/TMECH.2016.2614672CrossRefGoogle Scholar
  10. Liu ZX, Yuan C, Zhang YM, et al., 2016. A learningbased fault tolerant tracking control of an unmanned quadrotor helicopter. J Intell Rob Syst, 84(1-4):145–162. https://doi.org/10.1007/s10846-015-0293-0CrossRefGoogle Scholar
  11. Liu ZX, Yuan C, Yu X, et al., 2017. Retrofit fault-tolerant tracking control design of an unmanned quadrotor helicopter considering actuator dynamics. Int J Robust Nonl Contr, in press. https://doi.org/10.1002/rnc.3889Google Scholar
  12. Mallavalli S, Fekih A, 2018. A fault tolerant tracking control for a quadrotor UAV subject to simultaneous actuator faults and exogenous disturbances. Int J Contr, in press. https://doi.org/10.1080/00207179.2018.1484173Google Scholar
  13. Murray CC, Chu AG, 2015. The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp Res Part C Emerg Technol, 54:86–109. https://doi.org/10.1016/j.trc.2015.03.005CrossRefGoogle Scholar
  14. Park J, Sandberg IW, 1991. Universal approximation using radial-basis-function networks. Neur Comput, 3(2):246–257. https://doi.org/10.1162/neco.1991.3.2.246CrossRefGoogle Scholar
  15. Ríos H, Falcòn R, González OA, et al., 2018. Continuous sliding-modes control strategies for quad-rotor robust tracking: real-time application. IEEE Trans Ind Electron, 66(2):1264–1272. https://doi.org/10.1109/TIE.2018.2831191CrossRefGoogle Scholar
  16. Tao G, Chen SH, Tang XD, et al., 2004. State feedback designs for state tracking. In: Tao G, Chen SH, Tang XD, et al. (Eds.), Adaptive Control of Systems with Actuator Failures. Springer, London, p.15–54. https://doi.org/10.1007/978-1-4471-3758-0_2CrossRefGoogle Scholar
  17. Wang B, Ghamry KA, Zhang YM, 2016. Trajectory tracking and attitude control of an unmanned quadrotor helicopter considering actuator dynamics. 35th Chinese Control Conf, p.10795–10800. https://doi.org/10.1109/ChiCC.2016.7555068Google Scholar
  18. Wu EN, Zhang YM, Zhou KM, 2000. Detection, estimation, and accommodation of loss of control effectiveness. Int J Adapt Contr Signal Process, 14(7):775–795. https://doi.org/10.1002/1099-1115(200011)14:7<775:: AID-ACS621>3.0.CO;2-4CrossRefzbMATHGoogle Scholar
  19. Xiong JJ, Zhang GB, 2017. Global fast dynamic terminal sliding mode control for a quadrotor UAV. ISA Trans, 66:233–240. https://doi.org/10.1016/j.isatra.2016.09.019CrossRefGoogle Scholar
  20. Xu R, Ozguner U, 2006. Sliding mode control of a quadrotor helicopter. 45th IEEE Conf on Decision and Control, p.4957–4962. https://doi.org/10.1109/CDC.2006.377588Google Scholar
  21. Xu ZW, Nian XH, Wang HB, et al., 2017. Robust guaranteed cost tracking control of quadrotor UAV with uncertainties. ISA Trans, 69:157–165. https://doi.org/10.1016/j.isatra.2017.03.023CrossRefGoogle Scholar
  22. Yacef F, Bouhali O, Hamerlain M, et al., 2016. Observerbased adaptive fuzzy backstepping tracking control of quadrotor unmanned aerial vehicle powered by Li-ion batter. J Intell Robot Syst, 84(1-4):179–197. https://doi.org/10.1007/s10846-016-0345-0CrossRefGoogle Scholar
  23. Yuan C, Liu ZX, Zhang YM, 2015. UAV-based forest fire detection and tracking using image processing technique. Int Conf on Unmanned Aircraft Systems p.639–643. https://doi.org/10.1109/ICUAS.2017.7991306Google Scholar
  24. Zhang CH, Kovacs JM, 2012. The application of small unmanned aerial systems for precision agriculture: a review. Prec Agric, 13(6):693–712. https://doi.org/10.1007/s11119-012-9274-5CrossRefGoogle Scholar
  25. Zhang YM, Jiang J, 2002. Active fault-tolerant control system against partial actuator failures. IEE Proc Contr Theory Appl, 149(1):95–104. https://doi.org/10.1049/ip-cta:20020110CrossRefGoogle Scholar
  26. Zhang YM, Jiang J, 2008. Bibliographical review on reconfigurable fault-tolerant control systems. Ann Rev Contr, 32(2):229–252. https://doi.org/10.1016/j.arcontrol.2008.03.008CrossRefGoogle Scholar
  27. Zhong YJ, Zhang W, Zhang YM, 2018a. Active faulttolerant tracking control of a quadrotor UAV. Int Conf on Sensing, Diagnostics, Prognostics, and Control.Google Scholar
  28. Zhong YJ, Zhang YM, Zhang W, et al., 2018b. Robust actuator fault detection and diagnosis for a quadrotor UAV with external disturbances. IEEE Access, 6:48169–48180. https://doi.org/10.1109/ACCESS.2018.2867574CrossRefGoogle Scholar
  29. Zou Y, Zhu B, 2017. Adaptive trajectory tracking controller for quadrotor systems subject to parametric uncertainties. J Frankl Inst, 354(15):6724–6746. https://doi.org/10.1016/j.jfranklin.2017.08.027MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of AeronauticsNorthwestern Polytechnical UniversityXi’anChina
  2. 2.Department of Mechanical, Industrial and Aerospace EngineeringConcordia UniversityMontrealCanada

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