Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Maximum Torque Control of SynRM Drive with ALM-FNN Controller

ALM-FNN 제어기에 의한 SynRM 드라이브의 최대토크 제어

  • Ko, Jae-Sub (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Choi, Jung-Sik (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Lee, Jung-Ho (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Kim, Jong-Kwan (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Park, Ki-Tae (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Park, Byung-Sang (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Chung, Dong-Hwa (School of Information & Communication Engineering, Sunchon National Univ.)
  • 고재섭 (순천대학교 공과대학 정보통신공학부) ;
  • 최정식 (순천대학교 공과대학 정보통신공학부) ;
  • 이정호 (순천대학교 공과대학 정보통신공학부) ;
  • 김종관 (순천대학교 공과대학 정보통신공학부) ;
  • 박기태 (순천대학교 공과대학 정보통신공학부) ;
  • 박병상 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2006.04.20
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Abstract

The paper is proposed maximum torque control of SynRM 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 SynRM 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 verify the effectiveness of the ALM-FNN and ANN controller.

Keywords