Title
Multiapproximator-Based Fault-Tolerant Tracking Control for Unmanned Autonomous Helicopter With Input Saturation
Abstract
In this article, an adaptive neural fault-tolerant control (FTC) scheme is proposed for the medium-scale unmanned autonomous helicopter subject to external disturbance, actuator fault, and input saturation. Multiple approximators are constructed to handle the unknown terms and promote the control design. The nonlinear coupled function terms are approximated by virtue of the radial basis function neural networks. The unknown disturbance is tackled by the developed disturbance observer. Meanwhile, two auxiliary systems are introduced to handle the actuator fault and input saturation, respectively. In the framework of the backstepping method, a multiapproximator-based adaptive FTC strategy is presented, which assures the boundedness of all closed-loop system signals. Simulation results are presented to validate the availability of the designed controller.
Year
DOI
Venue
2022
10.1109/TSMC.2021.3131179
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Disturbance observer,fault-tolerant control (FTC),input saturation,tracking control,unmanned autonomous helicopter
Journal
52
Issue
ISSN
Citations 
9
2168-2216
0
PageRank 
References 
Authors
0.34
28
3
Name
Order
Citations
PageRank
Mou Chen1125159.31
Kun Yan200.34
Qing-xian Wu310510.76