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CLC number: TP273

On-line Access: 2019-01-30

Received: 2018-09-15

Revision Accepted: 2018-11-26

Crosschecked: 2019-01-08

Cited: 0

Clicked: 5783

Citations:  Bibtex RefMan EndNote GB/T7714


You-min Zhang


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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.1 P.95-106


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

Author(s):  Yu-jiang Zhong, Zhi-xiang Liu, You-min Zhang, Wei Zhang, Jun-yi Zuo

Affiliation(s):  School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China; more

Corresponding email(s):   yujiangzhong@hotmail.com

Key Words:  Model reference adaptive control, Neural network, Quadrotor, Fault-tolerant control, Fault detection and diagnosis

Yu-jiang Zhong, Zhi-xiang Liu, You-min Zhang, Wei Zhang, Jun-yi Zuo. Active fault-tolerant tracking control of a quadrotor with model uncertainties and actuator faults[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 95-106.

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%T Active fault-tolerant tracking control of a quadrotor with model uncertainties and actuator faults
%A Yu-jiang Zhong
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%A You-min Zhang
%A Wei Zhang
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T1 - Active fault-tolerant tracking control of a quadrotor with model uncertainties and actuator faults
A1 - Yu-jiang Zhong
A1 - Zhi-xiang Liu
A1 - You-min Zhang
A1 - Wei Zhang
A1 - Jun-yi Zuo
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1800570

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 loss-of-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.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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