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- W2904219526 abstract "In this paper, an adaptive neural discrete-time (ANDT) fractional-order tracking control scheme is proposed for an unmanned aerial vehicle system with prescribed performance in the presence of system uncertainties and unknown bounded disturbances based on a discrete-time disturbance observer (DTDO). The system uncertainties are handled using neural network (NN) approximation. To compensate for the adverse effects of unknown disturbances, an NN-based DTDO is designed. On the basis of the NN, the designed DTDO and the backstepping technology, an ANDT fractional-order control scheme with prescribed performance is developed. Then, the tracking errors are convergent under the proposed control scheme. Finally, the effectiveness of the proposed discrete-time control scheme is demonstrated by numerical simulation results." @default.
- W2904219526 created "2018-12-22" @default.
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- W2904219526 date "2021-02-01" @default.
- W2904219526 modified "2023-10-09" @default.
- W2904219526 title "Adaptive Neural Discrete-Time Fractional-Order Control for a UAV System With Prescribed Performance Using Disturbance Observer" @default.
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- W2904219526 doi "https://doi.org/10.1109/tsmc.2018.2882153" @default.
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