신경망을 이용한 제어기에 인가된 입력 신호의 추정

Input Signal Estimation About Controller Using Neural Networks

  • 손준혁 (경남대학교 대학원 전기공학과) ;
  • 서보혁 (경남대학교 전자전기공학부)
  • 발행 : 2005.08.01

초록

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

키워드

참고문헌

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