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• W4308273532 abstract "In this paper, an adaptive finite-time neural network tracking control problem for uncertain non-strict feedback systems is studied. For unknown nonlinear functions, they are approximated using neural networks. Under the framework of adaptive backstepping, a finite-time tracking controller based on a non-strict feedback system is designed. Unlike existing finite-time results, the proposed method can guarantee that the output of the system tracks the reference signal in a shorter time, and further, the tracking error is guaranteed to be confined to a small origin domain, while all signals in the closed-loop system are bounded and fast practical finite-time stablility. Finally, simulation example is given to exhibit the effectiveness of the presented technique." @default.
• W4308273532 created "2022-11-10" @default.
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• W4308273532 date "2022-10-14" @default.
• W4308273532 modified "2023-10-16" @default.
• W4308273532 title "Adaptive Finite-Time Neural Network Control for Non-strict Feedback Systems" @default.
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• W4308273532 doi "https://doi.org/10.1109/icist55546.2022.9926902" @default.
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