Adaptive regulation of uncertain chaos with dynamic neural networks
Tan Wen (谭文)ab, Wang Yao-Nan (王耀南)b, Zeng Zhao-Fu (曾照福)a, Huang Dan (黄丹)a, Zhou Shao-Wu (周少武)a
a Department of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; b College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Abstract A novel adaptive control for uncertain nonlinear chaotic system is presented. A dynamical neural networks is used to perform ‘black box' identification. Based on the identifier, the state feedback control is employed to drive the unknown chaotic system toward the desired target. Simulations show the derived control via the neuro-identifier turns out to be very effective.
Received: 16 July 2003
Revised: 11 August 2003
Accepted manuscript online:
Fund: Project supported by the National Natural Science Foundation of China(Grant Nos 60075008, 60102010) and by the Natural Science Foundation of Hunan Province (Grant Nos 02JJY2095, 03JJY3107).
Cite this article:
Tan Wen (谭文), Wang Yao-Nan (王耀南), Zeng Zhao-Fu (曾照福), Huang Dan (黄丹), Zhou Shao-Wu (周少武) Adaptive regulation of uncertain chaos with dynamic neural networks 2004 Chinese Physics 13 459
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