Abstract
In this paper, a novel design scheme of adaptive neural network controller design is proposed for a class of strict-feedback nonlinear systems. The problem of explosion of complexity in traditional backstepping design is avoided by utilizing dynamic surface control. In addition, parameter projection algorithms are employed to avoid the singularity of adaptive controller. By using Lyapunov method, the closed-loop system is shown to be semi-globally uniformly ultimately bounded, with arbitrary small tracking error by appropriately choosing design constants. The simulation results demonstrate the effectiveness of the proposed method.
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References
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)
Wang, D., Huang, J.: Adaptive neural network control for a class of uncertain nonlinear sustems in pure-feedback form. Automatica 38(8), 1365–1372 (2002)
Swaroop, D., Hedrick, J.K., Yip, P.P., Hedrick, J.K.: Dynamic surface control of nonlinear systems. In: Proc. ACC, Albuquerque, NM, pp. 3028–2034 (June 1997)
Yip, P.P., Hedrick, J.K.: Adaptive Dynamic surface control: A simplified algorithm for adaptive backstepping control of nonlinear systems. Int. J. Control 71(5), 959–979 (1998)
Dan, W., Jie, H.: Neural network-based adaptive dynamic surface control for a class of uncertain nonlinear systems in strict-feedback form. IEEE Trans. on Neural Network 16(1), 195–202 (2005)
Zhang, T., Ge, S.S., Hang, C.C.: Adaptive neural network control for strict-feedback nonlinear systems using backstepping design. Automatica 36, 1835–1846 (2000)
Zhang, T.P., Mei, J.D., Xia, Y., Yu, J.J.: Adaptive Fuzzy Control for Strict-feedback Nonlinear. In: Proceedings of the 5th World Congress on Intelligent Control and Automation, June 15-19 (2004)
Kanellakopoulos, I., Kokotovic, P.V., Marino, R.: Robustness of adaptive nonlinear control under an extended matching condition. In: Proc. IFAC Symp. Nonlinear Control System Design, Capri, Italy, pp. 192–197 (1989)
Krstic, M., Kanellakopoulos, I., Kokotovic, P.V.: Nonlinear and Adaptive Control Design. Wiley, New York (1995)
Ste, D., Annaswamy, A.M., Baillieul, J.: Adaptive control of nonlinear systems with a triangular structure. IEEE Trans. Autom. Control 39(7), 1411–1428 (1996)
Cybenko, G.: Approximation by super positions of a sigmoidal function. Math. C. Signals Syst. 2, 303–314 (1989)
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Li, H., Mei, J., Guo, Z. (2011). Neural Network-Based Adaptive Dynamic Surface Control of Nonlinear Strict-Feedback Systems. In: Jiang, L. (eds) Proceedings of the 2011, International Conference on Informatics, Cybernetics, and Computer Engineering (ICCE2011) November 19–20, 2011, Melbourne, Australia. Advances in Intelligent and Soft Computing, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25188-7_36
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DOI: https://doi.org/10.1007/978-3-642-25188-7_36
Publisher Name: Springer, Berlin, Heidelberg
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