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Fault-tolerant control of quadrotor unmanned aerial vehicle by using adaptive fuzzy T-S and linear matrix inversion approach
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  • Published: 09 April 2026

Fault-tolerant control of quadrotor unmanned aerial vehicle by using adaptive fuzzy T-S and linear matrix inversion approach

  • Muhammad Taimoor1,2,
  • Haixia Wang3,
  • Sameena Bibi4,
  • Chunyang Sheng3,
  • Umer Hameed Shah5,
  • Xiao Lu1,
  • Zhiguo Zhang3 &
  • …
  • Irfan Hussain6 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

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  • Engineering
  • Mathematics and computing

Abstract

In this research, a robust and adaptive fault-tolerant control approach is presented for the rejection of the unknown disturbances and faults existing in the quadrotor unmanned aerial vehicle sensors. The proposed approach is based on the hybrid utilization of the Fuzzy Takagi-Sugeno and linear matrix inversion control. Quadrotors are highly complex and nonlinear dynamic systems, which are vulnerable to unknown faults and disturbances, due to which the system performance may cause instability or degradation. To guarantee the stability of the system, an adaptive fuzzy T-S model is utilized to depict the nonlinear behavior of the system through a set of linear models based on fuzzy rules. The adaptive approach enables the controller to dynamically adjust based on the varying system conditions. A linear matrix inversion (LMI) control strategy is developed based on this model to effectively compute control inputs while maintaining system performance and stability. By integrating the approaches, the real-time faults are compensated without the requirement of fault diagnoses and isolation. The results of the simulation show that the suggested adaptive strategy shows robustness and strong resilience against unknown faults and disturbances, and ensures the stable flight compared to the conventional Fuzzy T-S controller, conventional linear matrix inversion (LMI) controller, and the techniques used in the literature. The results show the efficacy, effectiveness, and efficiency of the proposed approach for real-time UAV applications.To improve the safety and performance of nonlinear systems, it is suggested that the described method be integrated into fault-tolerant control (FTC).

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author(s) on reasonable request.

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Acknowledgements

Nil.

Funding

This work was supported by Khalifa University in collaboration with Dubai Future Labs through the Project "Underwater Maritime Monitoring" under Award 8475000016 and Award RC1-2018-KUCARS-8474000136.

Author information

Authors and Affiliations

  1. College of Energy Storage Technology, Shandong University of Science and Technology, Shandong, 266590, Qingdao, China

    Muhammad Taimoor & Xiao Lu

  2. Department of Avionics Engineering, College of Aeronautical Engineering (CAE), National University of Sciences and Technology (NUST), Risalpur, Pakistan

    Muhammad Taimoor

  3. School of Electrical Engineering and Automation, Shandong University of Science and Technology, Shandong, 266590, Qingdao, China

    Haixia Wang, Chunyang Sheng & Zhiguo Zhang

  4. Department of Mathematics, Air University, Islamabad, 44000, Pakistan

    Sameena Bibi

  5. Department of Mechanical Engineering and Artificial Intelligence Research Center, College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates

    Umer Hameed Shah

  6. Khalifa University Center for Autonomous Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, United Arab Emirates

    Irfan Hussain

Authors
  1. Muhammad Taimoor
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  2. Haixia Wang
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Contributions

Conceptualization, M.T. and X.L.; methodology, S.B.; software, C.S.; validation, U.H.S., I.H., and H.W.; formal analysis, M.T. and X.L.; investigation, Z.Z.; resources, X.L. and I.H.; data curation, M.T.J., Z.Z., and H.W.; writing-original draft preparation, M.T.; writing-review and editing and funding acquisition, I.H. and U.H.S. All authors have read and agreed to the current version of the manuscript.

Corresponding authors

Correspondence to Xiao Lu or Irfan Hussain.

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The authors declare no competing interests.

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Cite this article

Taimoor, M., Wang, H., Bibi, S. et al. Fault-tolerant control of quadrotor unmanned aerial vehicle by using adaptive fuzzy T-S and linear matrix inversion approach. Sci Rep (2026). https://doi.org/10.1038/s41598-026-46576-w

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  • Received: 20 October 2025

  • Accepted: 26 March 2026

  • Published: 09 April 2026

  • DOI: https://doi.org/10.1038/s41598-026-46576-w

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Keywords

  • Fuzzy T-S
  • Linear matrix inversion
  • Fault-tolerant control
  • Sensors
  • Quadrotor
  • Nonlinear system
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