Maximum Torque Control of SynRM using AFNIS(Adaptive Fuzzy Neuro Inference)

AFNIS를 이용한 SynRM의 최대토크 제어

  • Jung, Byung-Jin (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Ko, Jae-Sub (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Choi, Jung-Sik (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Jung, Chul-Ho (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Kim, Do-Yeon (School of Information & Communication Engineering. Sunchon National Univ.) ;
  • Chung, Dong-Hwa (School of Information & Communication Engineering. Sunchon National Univ.)
  • 정병진 (순천대학교 공과대학 정보통신공학부) ;
  • 고재섭 (순천대학교 공과대학 정보통신공학부) ;
  • 최정식 (순천대학교 공과대학 정보통신공학부) ;
  • 정철호 (순천대학교 공과대학 정보통신공학부) ;
  • 김도연 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2008.04.25

Abstract

The paper is proposed maximum torque control of SynRM drive using adaptive fuzzy neuro inference system(AFNIS) and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled AFNIS and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the AFNIS and ANN controller.

Keywords