Adaptive Control of Hyper-Chaotic Systems Based on Dynamic Structure RBF Neural Networks

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An adaptive control scheme based on neural networks is presented for control of hyper-chaotic systems. Parameters of neural networks and controllers are adjusted automatically to ensure the stability of the closed-loop system. Numerical simulation illustrates that the proposed control scheme is valid for hyper-chaotic system.

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Periodical:

Edited by:

Mohamed Othman

Pages:

2311-2314

Citation:

J. Wang et al., "Adaptive Control of Hyper-Chaotic Systems Based on Dynamic Structure RBF Neural Networks", Applied Mechanics and Materials, Vols. 229-231, pp. 2311-2314, 2012

Online since:

November 2012

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$38.00

[1] Lin T. C, Lee T. Y and Balas Valentina E: Chaos, Solitons&Fractals. Vol. 44 (2011), p.791.

[2] Chen D. Y., Liu Y. X and Ma X. Y: Nonlinear Dynamics. Vol. 67 (2012), p.893.

[3] Lin T. C, Lee T. Y: IEEE Transactions on Fuzzy Systems. Vol. 19 (2011) , p.623.

[4] S. Fabri, V. Kadirkamanathan: IEEE Transactions on Neural Networks. Vol. 7 (1996), p.1151.

[5] H. Sarimveis, A. Alexandridis, and G. Tsekouras et al: Industrial and Engineering Chemistry Research. Vol. 41 (2002), p.751.

[6] A. Alexandridis, H. Sarimveis and B. George: Neural Networks. Vol 16 (2003), p.1003.

[7] H. Ishibuchi, T. Murata and I.B. Türkşen: Fuzzy Sets and Systems. Vol. 89 (1997), p.135.

[8] T. Matsumoto, L.O. Chua and K. Kobayashi et al: IEEE Transactions on Circuits and Systems. Vol. 33 (1986 ), p.1143.