한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제5권4호
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  • Pages.163-169
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  • 2014
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  • 2233-4890(pISSN)
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  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
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Stable Tracking Control to a Non-linear Process Via Neural Network Model

  • Zhai, Yujia (Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University)
  • 투고 : 2014.08.12
  • 심사 : 2014.11.05
  • 발행 : 2014.12.31
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초록

A stable neural network control scheme for unknown non-linear systems is developed in this paper. While the control variable is optimised to minimize the performance index, convergence of the index is guaranteed asymptotically stable by a Lyapnov control law. The optimization is achieved using a gradient descent searching algorithm and is consequently slow. A fast convergence algorithm using an adaptive learning rate is employed to speed up the convergence. Application of the stable control to a single input single output (SISO) non-linear system is simulated. The satisfactory control performance is obtained.

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참고문헌

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