Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Fuzzy-Neural Control for Speed Control and estimation of SPMSM drive

SPMSM 드라이브의 속도제어 및 추정을 위한 퍼지-뉴로 제어

  • Nam Su-Myeong (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Lee Jung-Chul (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Lee Hong-Gyun (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Lee Young-Sil (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Park Bung-Sang (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Chung Dong-Hwa (School of Information & Communication Engineering, Sunchon National Univ.)
  • 남수명 (순천대학교 공과대학 정보통신공학부) ;
  • 이정철 (순천대학교 공과대학 정보통신공학부) ;
  • 이홍균 (순천대학교 공과대학 정보통신공학부) ;
  • 이영실 (순천대학교 공과대학 정보통신공학부) ;
  • 박병상 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2004.07.14
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Abstract

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. 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 theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

Keywords