Abstract
This paper presents the design of neural adaptive flight control systems for the longitudinal dynamics of hypersonic vehicle. By considering the coupling between thrust and pitch moment, the proposed control strategy is derived from the solutions of a series of fast dynamical equations, which are designed based on the back-stepping control and singularly perturbed system approach. The RBF neural networks are employed to approximate the unknown hypersonic dynamics. Simulation results are included to show the effectiveness of the neural adaptive control method.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Khalil, H.K.: Nonlinear Systems. Prentice Hall, Englewood Cliffs (2002)
Xu, H.J., Ioannou, P.A., Mirmirani, M.: Adaptive sliding mode control design for a hypersonic flight vehicle. J. Guid. Control. Dyn. 27(5), 829–838 (2004)
Ito, D., Ward, D., Valasek, J.: Robust dynamic inversion controller design and analysis for the X-38. In: AIAA Guidance,Navigation, and Control Conference, AIAA-2001-4380 (2001)
Wang, Q., Stengel, R.F.: Robust nonlinear control of a hypersonic aircraft. J. Guid. Control. Dyn. 23(4), 577–584 (2000)
Wallner, E.M., Well, K.H.: Nonlinear flight control design for the X-38 using CMAC neural networks. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, AIAA-2001-4042 (2001)
Xu, H.J., Mirmirani, M., Ioannou, P.A.: Robust neural adaptive control of a hypersonic aircraft. In: AIAA Guidance, Navigation, and Control Conference (2003)
Gao, D., Sun, Z.: Fuzzy tracking control design for hypersonic vehicles via T-S model. Sci. China-Inf. Sci. 54(3), 521–528 (2011)
Buschek, H., Calise, A.J.: Uncertainty modeling and fixed-order controller design for a hypersonic vehicle model. J. Guid. Control. Dyn. 20, 42–48 (1997)
Groves, K.P., Sigthorsson, D.O., Serrani, A., Yurkovich, S., Bolender, M.A., Doman, D.B.: Reference command tracking for a linearized model of an air-breathing hypersonic vehicle. In: AIAA Guidance, Navigation, and Control Conference, pp. 2901–2914. San Francisco, CA (2005)
Sigthorsson, D., Jankovsky, P., Serrani, A., Yurkovich, S., Bolender, M., Doman, D.B.: Robust linear output feedback control of an airbreathing hypersonic vehicle. J. Guid. Control. Dyn. 31, 1052–1066 (2008)
Kokotovic, P.V.: The joy of feedback: nonlinear and adaptive. IEEE Control. Syst. Maga. 12(7), 7–17 (1992)
Gao, D., Sun, Z., Xu, B.: Fuzzy adaptive control for pure-feedback system via time scale separation. Int. J. Control. Autom. Syst. 11(1), 147–158 (2013)
Gao, D., Sun, Z., Liu, J.: Dynamic inversion control for a class of pure-feedback systems. Asian J. Control. 14(2), 605–611 (2012)
Wang, C., Hillb, D.J., Ge, S.S., Chen, G.R.: An ISS-modular approach for adaptive neural control of pure-feedback systems. Automatica 42(5), 723–731 (2006)
Du, H.B., Shao, H.H., Yao, P.J.: Adaptive neural network control for a class of low-triangular-structured nonlinear systems. IEEE Trans. Neural Netw. Learn. Syst. 17(2), 509–514 (2006)
Ge, S.S., Wang, C.: Adaptive NN control of uncertain nonlinear pure-feedback systems. Automatica 38(4), 671–682 (2002)
Ge, S.S., Wang, C.: Direct adaptive NN control of a class of nonlinear systems. IEEE Trans. Neural Netw. Learn. Syst. 13(1), 214–221 (2002)
Swaroop, D., Hedrick, J.K., Yip, P.P., Gerdes, J.C.: Dynamic surface control for a class of nonlinear systems. IEEE Trans. Autom. Control. 45(10), 1893–1899 (2000)
Shin, D.H., Kim, Y.D.: Reconfigurable flight control system design using adaptive neural networks. IEEE Trans. Control Syst. Technol. 12(1), 87–100 (2004)
Kim, S.H., Kim, Y.S., Song, C.: A robust adaptive nonlinear control approach to missile autopilot design. Control. Eng. Pract. 12, 149–154 (2004)
Gao, D., Sun, Z., Luo, X., Du, T.: Fuzzy adaptive control for hypersonic vehicle via backstepping method. J. Contr. Theory Appl. 25, 805–810 (2008)
Xu, B., Sun, F., Liu, H., Ren, J.: Adaptive Kriging ontroller design for hypersonic flight vehicle via back-stepping. IET Contr. Theory Appl. 6(4), 487–497 (2012)
Gao, D., Sun, Z., Du, T.: Dynamic surface control for hypersonic aircraft using fuzzy logic system. In: IEEE International Conference on Automation and Logistics, pp. 2314–2319. IEEE Press, Piscataway (2007)
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, B., Wang, D., Sun, F., Shi, Z.: Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn. 70(1), 269–278 (2012)
Xu, B., Shi, Z.: Universal kriging control of hypersonic aircraft model using predictor model without back-stepping. IET Contr. Theory Appl. 7(4), 573–583 (2013)
Xu, B., Wang, D., Sun, F., Shi, Z.: Direct neural control of hypersonic flight vehicles with prediction model in discrete time. Neurocomputing 115(4), 39–48 (2013)
Marrison, C.I., Stengel, R.F.: Design of robust control system for a hypersonic aircraft. J. Guid. Control. Dyn. 21(1), 58–63 (1998)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gao, D., Wang, S. & Zhang, H. A Singularly Perturbed System Approach to Adaptive Neural Back-stepping Control Design of Hypersonic Vehicles. J Intell Robot Syst 73, 249–259 (2014). https://doi.org/10.1007/s10846-013-9992-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-013-9992-6