中国物理B ›› 2004, Vol. 13 ›› Issue (4): 459-463.doi: 10.1088/1009-1963/13/4/008

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Adaptive regulation of uncertain chaos with dynamic neural networks

王耀南1, 曾照福2, 黄丹2, 周少武2, 谭文3   

  1. (1)College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; (2)Department of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; (3)Department of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China; College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
  • 收稿日期:2003-07-16 修回日期:2003-08-11 出版日期:2004-04-22 发布日期:2004-04-20
  • 基金资助:
    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).

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    

  1. 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
  • Received:2003-07-16 Revised:2003-08-11 Online:2004-04-22 Published:2004-04-20
  • Supported by:
    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).

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摘要： 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.

关键词: chaos, adaptive control, identification, dynamical neural networks

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.

Key words: chaos, adaptive control, identification, dynamical neural networks

中图分类号:  (Control of chaos, applications of chaos)

  • 05.45.Gg
05.45.Pq (Numerical simulations of chaotic systems)