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


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



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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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