Skip to main content
SpringerLink
Log in

Fault Isolation and Fault Tolerant Control for the Uncertain Quadrotor UAV System

  • Regular Papers
  • Robot and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

In this paper, the fault isolation and fault diagnosis for the attitude control system of the quadrotor unmanned aerial vehicle (UAV) are shown, based on which the successive fault tolerant control (FTC) is also carried out. In most of modern literatures about the quadrotor UAV, the employed system dynamical models are established under ideal assumption conditions. However, system uncertainties of the quadrotor UAV system originating from modeling and other aspects, are seldom taken into account, which is deviated from the actual consequence. In this paper, a general dynamical model of the attitude control system of the quadrotor UAV is given, then for the aim to be more approximate to actual consequences, system uncertainties of state and input are considered. For the uncertain quadrotor UAV system, firstly, an observer method is employed to detect the fault location. Secondly, to diagnose the fault precisely, an adaptive observer with fault estimation term is employed. Lastly, on the basis of accurate fault estimation information, a sliding mode controller is employed to compensate the fault. Ultimately, the validity of the above mentioned methods is confirmed by numerical simulations.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. S. Hassan, A. Ali, and Y. Rafic, “A survey on quadrotors: Configurations, modeling and identification, control, collision avoidance, fault diagnosis and tolerant control,” IEEE Aerospace and Electronic Systems Magazine, vol. 33, no. 7, pp. 14–33, 2018.

    Article  Google Scholar 

  2. Y. L. Lin, B. Li, and D. Y. Wang, “Application of multi-rotor UAV patrol system in UHV infrastructure,” China Electric Power, vol. 50, no. 12, pp. 141–147, 2017.

    Google Scholar 

  3. C. Yuan, Z. X. Liu, and Y. M. Zhang, “Learning based smoke detection for unmanned aerial vehicles applied to forest fire surveillance,” Journal of Intelligent and Robotic Systems, vol. 10, no. 2, pp. 84–95, 2018.

    Google Scholar 

  4. H. Shahnazari and P. Mhaskar, “Actuator and sensor fault detection and isolation for nonlinear systems subject to uncertainty,” International Journal of Robust and Nonlinear Control, vol. 28, no. 6, pp. 1996–2013, 2018.

    Article  MathSciNet  Google Scholar 

  5. Z. H. Zhang, S. Li, H. Yan, and Q.-Y. Fan, “Sliding mode switching observer-based actuator fault detection and isolation for a class of uncertain systems,” Nonlinear Analysis: Hybrid Systems, vol. 33, pp. 322–335, 2019.

    MathSciNet  Google Scholar 

  6. W. Abid, A. Krifa, and N. Liouane, “Neural observer based small fault detection and isolation for uncertain nonlinear systems,” International Journal of Adaptive Control and Signal Processing, vol. 34, no. 5, pp. 677–702, 2020.

    Article  MathSciNet  Google Scholar 

  7. S. Amirkhani, A. Chaibakhsh, and A. Ghaffari, “Nonlinear robust fault diagnosis of power plant gas turbine using Monte Carlo based adaptive threshold approach,” ISA Transactions, vol. 100, pp. 171–184, 2019.

    Article  Google Scholar 

  8. P. Yang, Z. Liu, Y. Wang, and D. Li, “Adaptive sliding mode fault tolerant control for uncertain systems with time delay,” International Journal of Automation Technology, vol. 14, no. 2, pp. 337–345, 2020.

    Article  Google Scholar 

  9. L. Zhang and G. H. Yang, “Fault estimation based output feedback adaptive FTC for uncertain nonlinear systems with actuator faults,” IEEE Transactions on Industrial Electronics, vol. 67, no. 4, pp. 3065–3075, 2019.

    Article  Google Scholar 

  10. Y. Yan, L. Wu, N. Zhao, and R. Zhang, “Adaptive asymptotic tracking fault tolerant control of uncertain nonlinear systems with actuator failures and event triggered inputs,” International Journal of Control, Automation, and Systems, vol. 19, no. 3, pp. 1241–1251, 2021.

    Article  Google Scholar 

  11. J. Lee, H. Shin, and T. Kim, “Optimal combination of fault detection and isolation methods of integrated navigation algorithm for UAV,” International Journal of Aeronautical and Space Sciences, vol. 19, no. 3, pp. 694–710, 2018.

    Article  Google Scholar 

  12. E. D. Amato, V. A. Nardi, I. Notaro, and V. Scordamaglia, “A particle filtering approach for fault detection and isolation of UAV IMU sensors: Design, implementation and sensitivity analysis,” Sensors, vol. 21, no. 9, pp. 3066, 2021.

    Article  Google Scholar 

  13. J. X. Dong, Y. Wu, and G. H. Yang, “A new sensor fault isolation method for T-S fuzzy systems,” IEEE Transactions on Cybernetics, vol. 47, no. 9, pp. 2437–2447, 2017.

    Article  Google Scholar 

  14. M. F. Tariq, A. Q. Khan, M. Abid, and F. Mustafa, “Data driven robust fault detection and isolation of three-phase induction motor,” IEEE Transactions on Industrial Electronics, vol. 66, no. 6, pp. 4707–4715, 2018.

    Article  Google Scholar 

  15. S. Kanthalakshmi and M. Raghappriya, “Active fault diagnosis of 2 DOF helicopter using particle filter based log-likelihood ratio,” International Journal of Control, vol. 2021, no. 1, pp. 1–18, 2021.

    Google Scholar 

  16. A. Y. Ouadine, M. Mjahed, H. Ayad, and A. El Kari, “UAV quadrotor fault detection and isolation using artificial neural network and hammerstein-wiener model,” Studies in Informatics and Control, vol. 29, no. 3, pp. 317–328, 2020.

    Article  Google Scholar 

  17. T. Gao, W. Sheng, M. Zhou, B. Fang, and L. Zheng, “MEMS inertial sensor fault diagnosis using a CNN-based data-driven method,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 34, no. 14, 2059048, 2020.

    Article  Google Scholar 

  18. X. L. Ren, “Observer design for actuator failure of a quadrotor,” IEEE Access, vol. 8, pp. 152742–152750, 2020.

    Article  Google Scholar 

  19. Z. Zhang and J. X. Dong, “Fault tolerant containment control for IT2 fuzzy networked multi agent systems against denial-of-service attacks and actuator faults,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 52, no. 4, pp. 2213–2224, 2022.

    Article  Google Scholar 

  20. F. Wang, Z. Ma, H. Gao, C. Zhou, and C. Hua, “Disturbance observer based nonsingular fast terminal sliding mode fault tolerant control of a quadrotor UAV with external disturbances and actuator faults,” International Journal of Control, Automation, and Systems, vol. 20, no. 4, pp. 1122–1130, 2022.

    Article  Google Scholar 

  21. Y. X. Xue, Z. Y. Zhen, L. Q. Yang, and L. D. Wen, “Adaptive fault tolerant control for carrier based UAV with actuator failures,” Aerospace Science and Technology, vol. 2020, no. 107, 106227, 2020.

    Article  Google Scholar 

  22. P. Yang, Z. X. Wang, Z. Q. Zhang, and X. Hu, “Sliding mode fault tolerant control for a quadrotor with varying load and actuator fault,” Actuators, vol. 10, no. 323, pp. 1–17, 2021.

    Google Scholar 

  23. S. Ahmadizadeh, J. Zarei, and R. Hamid, “Robust unknown input observer design for linear uncertain time delay systems with application to fault detection,” Asian Journal of Control, vol. 16, no. 4, pp. 1006–1019, 2014.

    Article  MathSciNet  Google Scholar 

  24. J. J. Xiong and E. H. Zheng, “Position and attitude tracking control for a quadrotor UAV,” ISA Transactions, vol. 53, no. 3, pp. 725–731, 2014.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China

    Laifeng Zuo & Lina Yao

Authors
  1. Laifeng Zuo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lina Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lina Yao.

Ethics declarations

We declare that there is no competing financial interest or personal relationship that could have appeared to influence the work reported in this paper.

Additional information

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was supported by the National Natural Science Foundation of China under Grant 61973278 and the basic research projects of key scientific research projects of colleges, universities in Henan 21zx007 and the Excellent Youth Foundation of He’nan Scientific Committee 222300420019.

Laifeng Zuo received his B.S. degree in automation from Zhengzhou University, China in 2017, and an M.S. degree in control theory and engineering from Zhengzhou University, China in 2020. His research interests include nonlinear control, adaptive control, and system identification.

Lina Yao received her Ph.D. degree in control theory and control engineering from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 2006. From September 2007 to March 2008, she was a Research Fellow with the University of Science and Technology of Lille, France. She is currently a Professor with the School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China. Her research interests include fault diagnosis and fault tolerant control of dynamic systems, stochastic distribution control, and their applications.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zuo, L., Yao, L. Fault Isolation and Fault Tolerant Control for the Uncertain Quadrotor UAV System. Int. J. Control Autom. Syst. 22, 301–310 (2024). https://doi.org/10.1007/s12555-022-0249-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-022-0249-7

Keywords

Search

Navigation