Abstract
This paper investigates the discrete neural control for flight path angle and velocity of a generic hypersonic flight vehicle (HFV). First, strict-feedback form is set up for the attitude subsystem considering flight path angle, pitch angle, and pitch rate by altitude-flight path angle transformation. Secondly, the direct Neural Network (NN) control is proposed for attitude subsystem via back-stepping scheme. The direct design is employed for system uncertainty approximation with less online tuned NN parameters and there is no need to know the information of the upper bound of control gain during the controller design. Thirdly, with error feedback and NN design, the semiglobal uniform ultimate boundedness (SGUUB) stability is guaranteed of the closed-loop system. Similar NN control is applied on velocity subsystem. Finally, the feasibility of the proposed controller is verified by a simulation example.
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Ataei, A., Wang, Q.: Non-linear control of an uncertain hypersonic aircraft model using robust sum-of-squares method. IET Control Theory Appl. 6(2), 203–215 (2012)
Butt, W., Yan, L., Kendrick, A.: Adaptive dynamic surface control of a hypersonic flight vehicle with improved tracking. Asian J. Control 16(2), 1–12 (2014)
Chen, M., Ge, S., Ren, B.: Robust attitude control of helicopters with actuator dynamics using neural networks. IET Control Theory Appl. 4(12), 2837–2854 (2010)
Chen, M., Ge, S., Ren, B.B.: Adaptive tracking control of uncertain mimo nonlinear systems with input constraints. Automatica 47(3), 452–465 (2011)
Chen, M., Jiang, C., Wu, Q.: Disturbance-observer-based robust flight control for hypersonic vehicles using neural networks. Adv. Sci. Lett. 4(5), 1771–1775 (2011)
Dydek, Z., Annaswamy, A., Lavretsky, E.: Adaptive control and the NASA x-15-3 flight revisited. IEEE Control Syst. Mag. 30(3), 32–48 (2010)
Fiorentini, L., Serrani, A., Bolender, M., Doman, D.: Nonlinear robust adaptive control of flexible air-breathing hypersonic vehicles. J. Guid. Control Dyn. 32(2), 401–416 (2009)
Gao, D., Sun, Z.: Fuzzy tracking control design for hypersonic vehicles via ts model. Sci. China Ser. F 54(3), 521–528 (2011)
Gao, D., Sun, Z., Du, T.: Dynamic surface control for hypersonic aircraft using fuzzy logic system. In: IEEE International Conference on Automation and Logistics, Jinan, China, pp. 2314–2319 (2007)
Gao, D., Sun, Z., Du, T.: Discrete-time controller design for hypersonic vehicle via back-stepping. Control Decis. 24(3), 459–463 (2009)
Ge, S., Hang, C., Lee, T.: Stable Adaptive Neural Network Control. Springer, Amsterdam (2002)
Gibson, T., Crespo, L., Annaswamy, A.: Adaptive control of hypersonic vehicles in the presence of modeling uncertainties. In: American Control Conference, St. Louis, MO, USA, pp. 3178–3183 (2009)
Hu, X., Gao, H., Karimi, H., Wu, L., Hu, C.: Fuzzy reliable tracking control for flexible air-breathing hypersonic vehicles. Int. J. Fuzzy Syst. 13(4), 1–12 (2011)
Hu, Y., Sun, F., Liu, H.: Neural network-based robust control for hypersonic flight vehicle with uncertainty modelling. Int. J. Model. Identif. Control 11(1), 87–98 (2010)
Jiang, B., Gao, Z., Shi, P., Xu, Y.: Adaptive fault-tolerant tracking control of near-space vehicle using Takagi–Sugeno fuzzy models. IEEE Trans. Fuzzy Syst. 18(5), 1000–1007 (2010)
Kokotovic, P.: The joy of feedback: nonlinear and adaptive: 1991 bode prize lecture. IEEE Control Syst. Mag. 12, 7–17 (1991)
Liu, Y., Chen, C., Wen, G., Tong, S.: Adaptive neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems. IEEE Trans. Neural Netw. 22(7), 1162–1167 (2011)
Liu, Y., Wen, G., Tong, S.: Direct adaptive NN control for a class of discrete-time nonlinear strict-feedback systems. Neurocomputing 73(13–15), 2498–2505 (2010)
Park, J., Kim, S., Moon, C.: Adaptive neural control for strict-feedback nonlinear systems without backstepping. IEEE Trans. Neural Netw. 20(7), 1204–1209 (2009)
Parker, J., Serranit, A., Yurkovich, S., Bolender, M., Doman, D.: Control-oriented modeling of an air-breathing hypersonic vehicle. J. Guid. Control Dyn. 30(3), 856–869 (2007)
Wang, Q., Stengel, R.: Robust nonlinear control of a hypersonic aircraft. J. Guid. Control Dyn. 23(4), 577–585 (2000)
Wen, G., Liu, Y., Tong, S., Li, X.: Adaptive neural output feedback control of nonlinear discrete-time systems. Nonlinear Dyn. 65(1–2), 65–75 (2011)
Xu, B., Gao, D., Wang, S.: Adaptive neural control based on HGO for hypersonic flight vehicles. Sci. China Ser. F 54(3), 511–520 (2011)
Xu, B., Sun, F., Liu, H., Ren, J.: Adaptive Kriging controller design for hypersonic flight vehicle via back-stepping. IET Control Theory Appl. 6(4), 487–497 (2012)
Xu, B., Sun, F., Yang, C., Gao, D., Ren, J.: Adaptive discrete-time controller design with neural network for hypersonic flight vehicle via back-stepping. Int. J. Control 84(9), 1543–1552 (2011)
Xu, H., Mirmirani, M., Ioannou, P.: Adaptive sliding mode control design for a hypersonic flight vehicle. J. Guid. Control Dyn. 27(5), 829–838 (2004)
Yang, C., Ge, S., Xiang, C., Chai, T., Lee, T.: Output feedback NN control for two classes of discrete-time systems with unknown control directions in a unified approach. IEEE Trans. Neural Netw. 19(11), 1873–1886 (2008)
Zhu, Q., Zhang, T., Fei, S., Zhang, K., Li, T.: Adaptive neural control for a class of output feedback time delay nonlinear systems. Neurocomputing 72(7–9), 1985–1992 (2009)
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This work was supported by the National Science Foundation of China (Grants No: 61134004) and DSO National Laboratories of Singapore through a Strategic Project Grant (Project No. DSOCL10004).
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Xu, B., Wang, D., Sun, F. et al. Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn 70, 269–278 (2012). https://doi.org/10.1007/s11071-012-0451-x
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DOI: https://doi.org/10.1007/s11071-012-0451-x