Journal of the Institute of Electronics Engineers of Korea SC (전자공학회논문지SC)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Design of a Self-tuning Controller with a PID Structure Using Neural Network

신경회로망을 이용한 PID구조를 갖는 자기동조제어기의 설계

  • Cho, Won-Chul (Department of Computer Electronic, Gyeongdo provincial College) ;
  • Jeong, In-Gab (Department of Computer Electronic, Gyeongdo provincial College) ;
  • Shim, Tae-Eun (Department of Computer Electronic, Gyeongdo provincial College)
  • 조원철 (慶尙北道 道立 慶道大學 電子科) ;
  • 정인갑 (慶尙北道 道立 慶道大學 電子科) ;
  • 심태은 (慶尙北道 道立 慶道大學 電子科)
  • Published : 2002.11.01
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Abstract

This paper presents a generalized minimum-variance self-tuning controller with a PID structure using neural network which adapts to the changing parameters of the nonlinear system with nonminimum phase behavior and time delays. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation is done to adapt the nonlinear nonminimum phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct adaptive controller using neural network.

본 논문에서는 시간지연이 존재하고 시스템의 영점이 단위원 밖에 있으며 시스템 파라미터가 변하는 비선형 시스템에 적응하는 신경회로망을 이용한 PID구조를 갖는 일반화 최소분산 자기동조제어기를 제안한다. 신경회로망은 제어기 파라미터를 추정하며 제어 출력은 추정된 제어기 파라미터로부터 얻어진다. 제어 알고리듬의 타당성을 확인하기 위해 시간 지연이 있고 일정한 시간이 경과한 후 시스템의 파라미터가 변하는 비선형 비최소위상 시스템에 대해 컴퓨터 시뮬레이션을 하였다. 그리고 신경회로망을 이용한 직접 적응 제어기와 비교하였다.

Keywords

References

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