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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Adaptive Neural Control for Uncertain Attitude Dynamics of Near-Space Vehicles with Oblique Wing
verfasst von : Mou Chen, Qing-xian Wu
Erschienen in: Advances in Neural Networks – ISNN 2013
Verlag: Springer Berlin Heidelberg
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In this paper, the adaptive neural attitude control is developed for near-space vehicles with the oblique wing (NSVOW) via using the sliding mode disturbance observer technique. The radial basis function neural network (RBFNN) is employed to approximate the unknown system uncertainty. Then, the sliding mode disturbance observer is designed to estimate the unknown external disturbance and the unknown neural network approximation error. Using outputs of the sliding mode disturbance observer and the RBFNN, the adaptive neural attitude control is proposed for NSVOWs. The stability of the closed-loop system is proved using the Lyapunov analysis. Finally, simulation results are presented to illustrate the effectiveness of the proposed adaptive neural attitude control scheme.