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

The Institute of Electronics and Information Engineers (대한전자공학회)
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Estimation and Control of Speed of Induction Motor using FNN and ANN

FNN과 ANN을 이용한 유도전동기의 속도 제어 및 추정

  • Lee Jung-Chul (School of Information & Communication Engineering. Sunchon National University) ;
  • Park Gi-Tae (School of Information & Communication Engineering. Sunchon National University) ;
  • Chung Dong-Hwa (School of Information & Communication Engineering. Sunchon National University)
  • 이정철 (순천대학교 전기 전자정보통신공학부) ;
  • 박기태 (순천대학교 전기 전자정보통신공학부) ;
  • 정동화 (순천대학교 전기 전자정보통신공학부)
  • Published : 2005.11.01
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Abstract

This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

본 논문은 FNN과 ANN 제어기를 이용한 유도전동기의 속도 제어 및 추정을 제시한다. 먼저, PI 제어기에서 나타나는 문제점을 해결하기 위하여 퍼지제어와 신경회로망을 혼합 적용한 FN 제어기를 설계한다. 퍼지제어기의 강인성 제어와 신경회로망의 고도의 적응제어의 장점들을 접목한다. 다음은 ANN을 이용하여 유도전동기 드라이브의 속도 추정기법을 제시한다. 2층 구조를 가진 신경회로망에 BPA(Back Propagation Algorithm)를 적용하여 유도전동기 드라이브의 속도를 추정한다. 추정속도의 타당성을 입증하기 위하여 시스템을 구성하여 제어특성을 분석한다. 그리고 추정된 속도를 지령속도와 비교하여 전류제어와 공간벡터 PWM을 통하여 유도전동기의 속도를 제어한다. 본 연구에서 제시한 FNN과 ANN의 제어특성 및 추정성능을 분석하고 그 결과를 제시한다.

Keywords

References

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