Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Robust Adaptive Neural Network Controller with Dynamic Structure for Nonaffine Nolinear Systems

불확실한 비선형 계통에 대한 동적인 구조를 가지는 강인한 적응 신경망 제어기 설계

  • 박장현 (고려대학교 전기·전자·전파공학부) ;
  • 박귀태 (고려대학교 전기·전자·전파공학부)
  • Published : 2001.08.01
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Abstract

In adaptive neuro-control, neural networks are used to approximate unknown plant nonlinearities. Until now, most of the studies in the field of controller design for nonlinear system using neural network considers the affine system with fixed number of neurons. This paper considers nonaffine nonlinear systems and on-line variation of the number of neurons. A control law and adaptive laws for neural network weights are established so that the whole system is stable in the sense of Lyapunov. In addition, at the expense of th input, tracking error converges to the arbitrary small neighborhood of the origin. The efficiency of the proposed scheme is shown through simulations ofa simple nonaffine nonlinear system.

Keywords

References

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