×

Adaptive neural network control for a class of uncertain nonlinear systems in pure-feedback form. (English) Zbl 0998.93026

An adaptive neural network controller is designed for a class of SISO uncertain nonlinear systems. The backstepping design procedure is used. All signals in the closed-loop system are guaranteed to be uniformly ultimately bounded.

MSC:

93C40 Adaptive control/observation systems
92B20 Neural networks for/in biological studies, artificial life and related topics
93C10 Nonlinear systems in control theory
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Chen, F. C.; Khalil, H. K., Adaptive control of nonlinear systems using neural networks, International Journal of Control, 55, 6, 1299-1317 (1992) · Zbl 0759.93046
[2] Hornik, K., Approximation capabilities of multilayer feedforward networks, Neural Networks, 4, 251-257 (1991)
[3] Kanellakopoulos, I.; Kokotovic, P. V.; Morse, A. S., Systematic design of adaptive controllers for feedback linearizable systems, IEEE Transactions on Automatic Control, 36, 11, 1241-1253 (1991) · Zbl 0768.93044
[4] Krstic, M.; Kanellakopoulos, I.; Kokotovic, P. V., Nonlinear and adaptive control design (1995), Wiley: Wiley New York · Zbl 0763.93043
[5] Kwan, C.; Lewis, F. L.; Dawson, D. M., Robust neural-net control of rigid-link electrically driven robots, IEEE Transactions on Neural Networks, 9, 4, 581-588 (1998)
[6] Kwan, C.; Lewis, F. L., Robust backstepping control of nonlinear systems using neural networks, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, 30, 6, 753-766 (2000)
[7] Lewis, F. L.; Yesildirek, A.; Liu, K., Multilayer neural-net robot controller with guaranteed tracking performance, IEEE Transactions on Neural Networks, 7, 2, 388-399 (1996)
[8] Polycarpou, M. M., & Ioannou, P. A. (1992). Modeling, identification and stable adaptive of continuous-time nonlinear dynamical systems using neural networks. Proceedings of the 1992 American control conference; Polycarpou, M. M., & Ioannou, P. A. (1992). Modeling, identification and stable adaptive of continuous-time nonlinear dynamical systems using neural networks. Proceedings of the 1992 American control conference
[9] Polycarpou, M. M., Stable adaptive neural scheme for nonlinear systems, IEEE Transactions on Neural Networks, 7, 3, 447-451 (1996) · Zbl 0846.93060
[10] Polycarpou, M. M.; Mears, M. J., Stable adaptive tracking of uncertainty systems using nonlinearly parameterized on-line approximators, International Journal of Control, 70, 3, 363-384 (1998) · Zbl 0945.93563
[11] Sanner, R. M.; Slotine, J. E., Gaussian networks for direct adaptive control, IEEE Transactions on Neural Networks, 3, 6, 837-863 (1992)
[12] Seto, D.; Annaswamy, A. M.; Baillieul, J., Adaptive control of nonlinear systems with a triangular structure, IEEE Transactions on Automatic Control, 39, 7, 1411-1428 (1994) · Zbl 0806.93034
[13] Zhang, T.; Ge, S. S.; Hang, C. C., Design and performance analysis of a direct adaptive controller for nonlinear systems, Automatica, 35, 11, 1809-1817 (1999) · Zbl 0934.93039
[14] Zhang, T.; Ge, S. S.; Hang, C. C., Adaptive neural network control for strict-feedback nonlinear systems using backstepping design, Automatica, 36, 12, 1835-1846 (2000) · Zbl 0976.93046
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.