On the Temperature Control of Boiler using Neural Network Predictive Controller

신경회로망의 예측제어기를 이용한 보일러의 온도제어에 관한 연구

  • 엄상희 (동아대학교 전기공학과) ;
  • 이권순 (동아대학교 전기공학과) ;
  • 배종일 (부산공업대학교 전기공학과)
  • Published : 1995.07.20

Abstract

The neural network predictive controller(NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output(Neural Network Predictor) and the other one is for control the plant(Neural Network Controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and prediction error. The NNP forecasts the future output based upon the current control input and the estimated control output. The method is applied to the control of temperature in boiler systems. The proposed NNPC is compared with the other conventional control methods such as PID controller, neural network controller with specialized learning architecture, and one-step-ahead controller. The computer simulation and experimental results show that the proposed method has better performances than the other methods.

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