Output feedback fault-tolerant control for a class of nonlinear systems via dynamic gain and neural network

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Abstract

In this paper, by combining the dynamic gain and the self-adaptive neural network, an output feedback fault-tolerant control method was proposed for a class of nonlinear uncertain systems with actuator faults. First, the dynamic gain was introduced and the coordinate transformation of the state variables of the system was performed to design the corresponding state observers. Then, the observer-based output feedback controller was designed through the back-stepping method. The output feedback control method based on the dynamic gain can solve the adaptive fault-tolerant control problem when there are simple nonlinear functions with uncertain parameters in the system. For the more complex uncertain nonlinear functions in the system, in this paper, a single hidden layer neural network was used for compensation and the fault-tolerant control was realized by combining the dynamic gain. Finally, the height and posture control system of the unmanned aerial vehicle with actuator faults was taken as an example to verify the effectiveness of the proposed method.

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Xi, X., Liu, T., Zhao, J., & Yan, L. (2020). Output feedback fault-tolerant control for a class of nonlinear systems via dynamic gain and neural network. Neural Computing and Applications, 32(10), 5517–5530. https://doi.org/10.1007/s00521-019-04583-1

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