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Synchronization Scheme for Uncertain Chaotic Systems via RBF Neural Network |
| CHEN Mou1;JIANG Chang-Sheng1;WU Qing-Xian1;CHEN Wen-Hua2 |
| 1Automation College, Nanjing University of Aeronautics and Astronautics, Nanjing 2100162Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK |
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| Cite this article: |
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CHEN Mou, JIANG Chang-Sheng, WU Qing-Xian et al 2007 Chin. Phys. Lett. 24 890-893 |
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Abstract A sliding mode adaptive synchronization controller is presented with a neural network of radial basis function (RBF) for two chaotic systems. The uncertainty of the synchronization error system is approximated by the RBF neural network. The synchronization controller is given based on the output of the RBF neural network. The proposed controller can make the synchronization error convergent to zero in 5s and can overcome disruption of the uncertainty of the system and the exterior disturbance. Finally, an example is given to illustrate the effectiveness of the proposed synchronization control method.
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| Keywords:
05.45.Pq
05.45.Gg
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Received: 18 September 2006
Published: 26 March 2007
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| PACS: |
05.45.Pq
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(Numerical simulations of chaotic systems)
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05.45.Gg
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(Control of chaos, applications of chaos)
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