Adaptive neural control for uncertain attitude dynamics of near-space vehicles with oblique wing

Authors:
Mou Chen;Qing-xian Wu
Affiliations:
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China;College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Year:
2013

Citing 3
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Abstract

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.