Title
Adaptive fault-tolerant tracking control of flying-wing unmanned aerial vehicle with system input saturation and state constraints
Abstract
In this paper, an adaptive fault-tolerant attitude tracking controller based on reinforcement learning is developed for flying-wing unmanned aerial vehicle subjected to actuator faults and saturation. At first, the attitude dynamic model is separated into two dynamic subsystems as slow and fast dynamic subsystems based on the principle of time scale separation. Secondly, backstepping technique is adopted to design the controller. For the purpose of attitude angle constraints, the control technique based on Barrier Lyapunov is used to design controller of slow dynamic subsystem. Considering the optimization of the fast dynamic subsystem, this paper introduces an adaptive reinforcement learning control method in which neural network is used to approximate the long-term performance index and lumped fault dynamic. It is shown that this control algorithm can satisfy the requirements of attitude tracking subjected to the control constraints and the stability of the system is proved from Lyapunov stability theory. The simulation results demonstrate that the developed fault-tolerant scheme is useful and has more smooth control effect compared with fault-tolerant controller based on sliding mode theory.
Year
DOI
Venue
2022
10.1177/01423312211027037
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
Keywords
DocType
Volume
Aircraft control, fault-tolerant control, neural networks, nonlinear control, flight control
Journal
44
Issue
ISSN
Citations 
4
0142-3312
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Zhen Li100.34
Xi Chen233370.76
Mingyang Xie300.34
Zhenhua Zhao400.34