한국지능시스템학회논문지 (Journal of the Korean Institute of Intelligent Systems)

  • 제14권1호
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  • Pages.118-124
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  • 2004
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  • 1976-9172(pISSN)
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  • 2288-2324(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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Wavelet Neural Network Based Indirect Adaptive Control of Chaotic Nonlinear Systems

  • Choi, Yoon-Ho (School of Electronic Engineering, Kyonggi University) ;
  • Choi, Jong-Tae (School of Electrical and Electronic Engineering, Yonsei University) ;
  • Park, Jin-Bae (School of Electrical and Electronic Engineering, Yonsei University)
  • 발행 : 2004.02.01
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초록

In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.

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참고문헌

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