Auto-tuning of PID controller using Neural Networks and Model Reference Adaptive control

신경망을 이용한 PID 제어기의 자동동조 및 기준모델 적응제어

  • Kim, S.T. (Dept. of Electronics engineering, Univ. of Inchon) ;
  • Kim, J.S. (Dept. of Electronics engineering, Univ. of Inchon) ;
  • Seo, Y.O. (Dept. of Electronics engineering, Univ. of Inchon) ;
  • Park, S.J. (Dept. of Electronics engineering, Univ. of Inchon) ;
  • Hong, Y.C. (Dept. of Electronics engineering, Univ. of Inchon)
  • 김순태 (인천대학교 전자공학과 제어계측 연구실) ;
  • 김종석 (인천대학교 전자공학과 제어계측 연구실) ;
  • 서양오 (인천대학교 전자공학과 제어계측 연구실) ;
  • 박세진 (인천대학교 전자공학과 제어계측 연구실) ;
  • 홍연찬 (인천대학교 전자공학과 제어계측 연구실)
  • Published : 2000.07.17

Abstract

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.

Keywords