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Model-based Fault Detection and Identification of a Quadrotor with Rotor Fault

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Abstract

Fault detection and identification (FDI) is a challenging and critical process when dealing with nonlinear, unstable, and underactuated systems such as multirotor. This article presents a novel two-stage structure for a fault-tolerant FDI approach for a quadrotor with an actuator fault. The FDI algorithm generates residual signals for fault detection using a model-based approach based on the parity space. The basic idea behind this approach is to leverage measurement coherence by generating residuals via linear combinations of measurement outputs and control inputs over a finite window. The parity vector is generated using the states of the faulty system, which have been filtered using an extended Kalman filter, the inputs, and the healthy quadrotor model. To detect and identify the actuator's partial fault, the residual signal is examined using the exponential forgetting factor recursive least square method. Real-time testbed experiments are used to determine the FDI algorithm's performance and to demonstrate the proposed algorithm's effectiveness in identifying a quadrotor's rotor fault.

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References

  1. Turan V, Avşar E, Asadi D, Aydın EA (2021) Image processing based autonomous landing zone detection for a multi-rotor drone in emergency situations. Turk J Eng 5(4):193–200. https://doi.org/10.31127/tuje.744954

    Article  Google Scholar 

  2. Ducard GJ (2009) Fault-tolerant flight control and guidance systems: practical methods for small unmanned aerial vehicles. Springer (ISBN 978-1-84882-560-4)

    Book  MATH  Google Scholar 

  3. Asadi D, Ahmadi K, Nabavi-chashmi S, Tutsoy O (2021) Controllability of multi-rotors under motor fault effect. Artibilim: Adana Alparslan Turkes Bilim ve Teknoloji Universitesi Fen Bilimleri Dergisi 4(2):24–43

    Google Scholar 

  4. Mazeh H, Saied M, Shraim H, Francis C (2018) Fault-tolerant control of an hexarotor unmanned aerial vehicle applying outdoor tests and experiments. Int Fed Autom Control 51:312–317

    Google Scholar 

  5. Nguyen C, Xuan Mung N, Hong SK (2019) Actuator fault detection and fault-tolerant control for hexacopter. Sensors 19:4721. https://doi.org/10.3390/s19214721

    Article  Google Scholar 

  6. Lopez-Franco C, Gomez J, Alanis A, Daniel N, Villasenor C (1865) Visual servoing for an autonomous hexarotor using a neural network based PID controller. Sensors 2017:17. https://doi.org/10.3390/s17081865

    Article  Google Scholar 

  7. Asadi D, Sabzehparvar M, Talebi HA (2013) Damaged airplane flight envelope and stability evaluation. Aircr Eng Aerosp Technol 85(3):186–198. https://doi.org/10.1108/00022661311313623

    Article  Google Scholar 

  8. Asadi D, Atkins EM (2017) Multi-objective weight optimization for trajectory planning of an airplane with structural damage. J Intell Rob Syst. https://doi.org/10.1007/s10846-017-0753-9

    Article  Google Scholar 

  9. Asadi D, Sabzehparvar M, Atkins EM, Talebi HA (2014) Damaged airplane trajectory planning based on flight envelope and stability of motion primitives. J Aircr 51(6):1740–1757. https://doi.org/10.2514/1.C032422

    Article  Google Scholar 

  10. Zuo Z, Liu C, Han Q-L, Song J (2022) Unmanned aerial vehicles: control methods and future challenges. IEEE/CAA J Autom Sin 9(4):601–614. https://doi.org/10.1109/JAS.2022.105410

    Article  Google Scholar 

  11. Baldini A, Felicetti R, Freddi A et al (2020) Actuator fault-tolerant control architecture for multirotor vehicles in presence of disturbances. J Intell Robot Syst 99:859–874. https://doi.org/10.1007/s10846-020-01150-y

    Article  Google Scholar 

  12. Lanzon A, Freddi A, Longhi S (2014) Flight control of a quadrotor vehicle subsequent to a rotor failure. J Guid Control Dyn 37:580–591

    Article  Google Scholar 

  13. Zhang M, Chamseddine A, Rabbath CA, Gordon BW, Su C-Y, Rakheja S, Fulford C, Apiarian J, Gosselin P (2013) Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed. J Franklin Inst 350:2396–2422

    Article  MATH  Google Scholar 

  14. Ahmadi K, Asadi D, Pazooki F (2017) Nonlinear L1 adaptive control of an airplane with structural damage. Proc Inst Mech Eng Part G J Aerosp Eng 233(1):341–353

    Article  Google Scholar 

  15. Asadi D, Ahmadi K (2020) Nonlinear Robust adaptive control of an airplane with structural damage. Proc Inst Mech Eng Part G J Aerosp Eng. https://doi.org/10.1177/0954410020926618

    Article  Google Scholar 

  16. Asadi D, Bagherzadeh S (2017) Nonlinear adaptive sliding mode tracking control of an airplane with wing damage. Proc IMECHE Part G J Aerosp Eng 232(8):1405–1420

    Article  Google Scholar 

  17. Yang P, Liu Z, Li D, Jiang B, Zhu J (2021) Sliding mode prediction fault-tolerant control method for multi-delay uncertain discrete system with sensor fault. Trans Inst Meas Control 43(7):1519–1530. https://doi.org/10.1177/0142331220953334

    Article  Google Scholar 

  18. Hu C, Zhang Z, Zhou X, Wang N (2020) Command filter-based fuzzy adaptive nonlinear sensor-fault tolerant control for a quadrotor unmanned aerial vehicle. Trans Inst Meas Control 42(2):198–213. https://doi.org/10.1177/0142331219865377

    Article  Google Scholar 

  19. Asadi D, Ahmadi K, Nabavi SY (2021) Fault-tolerant trajectory tracking control of a quadcopter in presence of a motor fault. Int J Aeronaut Space Sci. https://doi.org/10.1007/s42405-021-00412-9

    Article  Google Scholar 

  20. Bagherzadeh SA, Asadi D (2017) Detection of the ice assertion on aircraft using empirical mode decomposition enhanced by multi-objective optimization. Mech Syst Signal Process 88:9–24. https://doi.org/10.1016/j.ymssp.2016.11.013

    Article  Google Scholar 

  21. Lu P, van Kampen E-J (2015) Active fault-tolerant control for quadrotors subjected to a complete rotor failure. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, pp 4698-4703, https://doi.org/10.1109/IROS.2015.7354046

  22. van Schijndel BS, Sun S, de Visser C (2021) Fast fault detection on a quadrotor using onboard sensors and a Kalman filter approach. arXiv-CS-Robotics (IF), https://doi.org/10.48550/arXiv.2102.06439.

  23. Amoozgar M, Chamseddine H, Zhang Y (2013) ‘Experimental test of a two-stage Kalman filter for actuator fault detection and diagnosis of an unmanned quadrotor helicopter.’ J Intell Robot Syst 70:107–117

    Article  Google Scholar 

  24. Cen Z, Noura H, Susilo BT, Younes YA (2014) Robust fault diagnosis for quadrotor UAVs using adaptive Thau observer. J Intell Robot Syst 73(1–4):573–588

    Article  Google Scholar 

  25. Avram RC, Zhang X, Muse J (2017) Quadrotor actuator fault diagnosis and accommodation using nonlinear adaptive estimators’. IEEE Trans Control Syst Technol 25(6):2219–2226

    Article  Google Scholar 

  26. Frangenberg M, Stephan J, Fichter W (2015) Fast actuator fault detection and reconfiguration for multi-copters, (AIAA 2015–1766). In: Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 2015

  27. Han W, Wang Z, Yi S (2018) Fault estimation for a quadrotor unmanned aerial vehicle by integrating the parity space approach with recursive least squares. Proc Inst Mech Eng G J Aerosp Eng 232(4):783–796

    Article  Google Scholar 

  28. Odendaal HM, Jones T (2014) Actuator fault detection and isolation: An optimized parity space approach. Control Eng Pract 26:222–232

    Article  Google Scholar 

  29. Varrier S, Koenig D, Martinez JJ (2014) Robust fault detection for uncertain unknown inputs LPV system. Control Eng Pract 22:125–134

    Article  Google Scholar 

  30. Gertler JJ (1998) Fault detection and diagnosis in engineering systems, 1st edn. Marcel Dekker Inc., New York (0-8247-9427-3)

    Google Scholar 

  31. Chang HL (2015) Integrated Approaches to handle UAV actuator fault, Cranfield University, Ph.D. thesis

  32. Yuksek B, Ure NK, Caliskan F, Inalhan G (2017) Fault tolerant heading control system design for Turac unmanned aerial vehicle. Trans Inst Meas Control 39(3):267–276. https://doi.org/10.1177/0142331216645179

    Article  Google Scholar 

  33. Amadi CM (2018) Design and implementation of model predictive control on Pixhawk flight controller, Stellenbosch University, Master thesis

  34. Asadi D (2022) Partial engine fault detection and control of a quadrotor considering model uncertainty. Turk J Eng 6(2):106–117. https://doi.org/10.31127/tuje.843607

    Article  MathSciNet  Google Scholar 

  35. Patton RJ, Chen J A review of parity space approaches to fault diagnosis applicable to aerospace systems, Department of Electronics, University of York, UK. In: AIAA 92–4538

  36. Guzman-Rabasa JA, Lopez EF, Gonzalez CBM (2019) Actuator fault detection and isolation on a quadrotor unmanned aerial vehicle modeled as a linear parameter varying system. Meas Control 52(9–10):1228–1239

    Article  Google Scholar 

Download references

Funding

This research was supported by the Scientific Research Project Unit (BAP) of Adana Alparslan Türkeş Science and Technology University with project number 19119002.

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  1. Department of Aerospace Engineering, Adana Alparslan Türkeş Science and Technology University, 01250, Adana, Turkey

    Davood Asadi

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  1. Davood Asadi
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Correspondence to Davood Asadi.

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Asadi, D. Model-based Fault Detection and Identification of a Quadrotor with Rotor Fault. Int. J. Aeronaut. Space Sci. 23, 916–928 (2022). https://doi.org/10.1007/s42405-022-00494-z

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  • DOI: https://doi.org/10.1007/s42405-022-00494-z

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