L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system
L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system
- New search for: Zhou, Yan
- Further information on Zhou, Yan:
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https://orcid.org/0000-0003-4998-2490
- New search for: Liu, Huiying
- New search for: Guo, Huijuan
- New search for: Li, Jing
- New search for: Zhou, Yan
- Further information on Zhou, Yan:
-
https://orcid.org/0000-0003-4998-2490
- New search for: Liu, Huiying
- New search for: Guo, Huijuan
- New search for: Li, Jing
In this article, a L1 neural network adaptive fault-tolerant controller is exploited for an unmanned aerial vehicle attitude control system in presence of nonlinear uncertainties, such as system uncertainties, external disturbances, and actuator faults. A nonlinear dynamic inversion controller with sliding mode control law is designed as the outer-loop controller to track the attitude angles quickly and accurately which reduces dependence on model accuracy. A L1 neural network adaptive controller of the inner loop is introduced to compensate the nonlinear uncertainties and have a good attitude tracking. The radial basis function neural network technique is introduced to approximate a lumped nonlinear uncertainty and guarantee the stability and transient performance of the closed-loop system, instead of converting it to a half-time linear system by the parametric linearization method. Simulation results demonstrate the effectiveness of the proposed controller.
Document information
L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system
2021-10-01
12 pages
Article (Journal)
Electronic Resource
English
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