Abstract
In this paper, a robust adaptive neural network synchronization controller is proposed for two chaotic systems with input time delay and uncertainty. The studied chaotic system may possess a wide class of nonlinear time-delayed input uncertainty. The radial basis function (RBF) neural network is used to approximate the unknown continuous bounded function item of the time delay uncertainty via appropriate weight value updated law. With the output of RBF neural network, a robust adaptive synchronization control scheme is presented for the time delay uncertain chaotic system. Finally, a simulation example is used to illustrate the effectiveness of the proposed synchronization control scheme.
Original language | English |
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Pages (from-to) | 2716-2724 |
Number of pages | 9 |
Journal | Chaos, Solitons and Fractals |
Volume | 41 |
Issue number | 5 |
DOIs | |
Publication status | Published - 15 Sept 2009 |
ASJC Scopus subject areas
- Statistical and Nonlinear Physics
- General Mathematics
- General Physics and Astronomy
- Applied Mathematics