Maximum Torque Control of IPMSM with ALM-FNN Controller

ALM-FNN 제어기에 의한 IPMSM의 최대토크 제어

  • Nam, Su-Myeong (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.) ;
  • 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) ;
  • 고재섭 (순천대학교 공과대학 정보통신공학부) ;
  • 최정식 (순천대학교 공과대학 정보통신공학부) ;
  • 박병상 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2005.10.20

Abstract

The paper is proposed maximum torque control of IPMSM drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) controller 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 IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verily the effectiveness of the ALM-FNN and ANN controller.

Keywords