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- W3162181148 endingPage "102686" @default.
- W3162181148 startingPage "102686" @default.
- W3162181148 abstract "In this paper, a composite learning tracking control scheme is developed for underactuated autonomous underwater vehicles (AUVs) in the presence of unknown dynamics and time-varying disturbances. Line-of-sight (LOS) tracking control is employed to handle the underactuation of AUVs. The unknown dynamics of the AUVs are approximated by adaptive neural networks (NNs). The serial-parallel estimation models are built to obtain the prediction errors. Both the prediction errors and the tracking errors are employed to design the composite weights updating law. Nonlinear disturbance observers based on composite learning control are constructed to estimate time-varying disturbances. The stability analysis via the Lyapunov method indicates that the uniformly ultimate boundedness of all signals of the AUV trajectory tracking close-loop control system. The simulation results on an AUV verify the effectiveness and the superiority of the proposed composite learning tracking control scheme." @default.
- W3162181148 created "2021-05-24" @default.
- W3162181148 creator A5030076255 @default.
- W3162181148 creator A5069997489 @default.
- W3162181148 date "2021-07-01" @default.
- W3162181148 modified "2023-10-18" @default.
- W3162181148 title "Composite learning tracking control for underactuated autonomous underwater vehicle with unknown dynamics and disturbances in three-dimension space" @default.
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- W3162181148 doi "https://doi.org/10.1016/j.apor.2021.102686" @default.
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