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.
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References
Du, Y.L., Wu, Q.X., Jiang, C.S., et al.: Adaptive functional link network control of near-space vehicles with dynamical uncertainties. Journal of System Engineering and Electronics 21(5), 868–876 (2010)
Jiang, B., Gao, Z.F., Shi, P., et al.: Adaptive fault-tolerant tracking control of near space vehicle using Takagi-Sugeno fuzzy models. IEEE Transactions on Fuzzy System 18(5), 1000–1007 (2010)
Xu, Y.F., Jiang, B., Tao, G., et al.: Fault tolerant control for a class of nonlinear systems with application to near space vehicle. Circuits System Signal Process 30(3), 655–672 (2011)
Desktop Aeronautics, Inc., Oblique Flying Wing: An Introduction and Whiter Paper
Enns, D.F., Bugajski, D.J., Klepl, M.J.: Flight control for the F-8 oblique wing research aircraft. In: American Control Conferrence, Minneapolis, USA, pp. 81–86 (June 1987)
Clark, R.N., LeTron, X.J.Y.: Oblique wing aircraft flight control system. Journal of Aircraft 12(2), 201–208 (1989)
Pang, J., Mei, R., Chen, M.: Modeling and control for near-Space vehicles with oblique wing. In: WCICA 2012, pp. 1773–1778 (2012)
Chen, M., Ge, S.S., How, B.: Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities. IEEE Transactions on Neural Networks 21(5), 796–812 (2010)
Chen, M., Ge, S.S., Ren, B.B.: Robust attitude control of helicopters with actuator dynamics using neural networks. IET Control Theory & Application 4(12), 2837–2854 (2010)
Chen, M., Jiang, C.S., Jiang, B., Wu, Q.X.: Robust control for a class of uncertain time delay nonlinear system based on sliding mode observer. Neural Computing and Applications 19, 945–951 (2010)
Chen, M., Wu, Q.X., Cui, R.X.: Terminal sliding mode tracking control for a class of SISO uncertain nonlinear systems. ISA Transaction 52, 198–206 (2013)
Chen, M., Jiang, B.: Robust attitude control of near space vehicles with time-varying disturbances. International Journal of Control, Automation, and Systems 11, 82–187 (2013)
Hall, C.E., Shtessel, Y.B.: Sliding mode disturbance observer-based control for a reusable launch vehicle. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, pp. 1–26 (August 2005)
Lu, Y.S.: Sliding-mode disturbance observer with switching-gain adaptation and its application to optical disk drives. IEEE Transactions on Industrial Electronics 56(9), 3743–3750 (2009)
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Chen, M., Wu, Qx. (2013). Adaptive Neural Control for Uncertain Attitude Dynamics of Near-Space Vehicles with Oblique Wing. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_24
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DOI: https://doi.org/10.1007/978-3-642-39068-5_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39067-8
Online ISBN: 978-3-642-39068-5
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