Adaptive NFC Control for High Performance Control of SPMSM Drive

SPMSM 드라이브의 고성능 제어를 위한 적응 NFC 제어

  • 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.) ;
  • Nam Su-Myeong (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Park Gi-Tae (School of Information & Communication Engineering, Sunchon National Univ.) ;
  • Chung Dong-Hwa (School of Information & Communication Engineering, Sunchon National Univ.)
  • 이정철 (순천대학교 공과대학 정보통신공학부) ;
  • 이홍균 (순천대학교 공과대학 정보통신공학부) ;
  • 이영실 (순천대학교 공과대학 정보통신공학부) ;
  • 남수명 (순천대학교 공과대학 정보통신공학부) ;
  • 박기태 (순천대학교 공과대학 정보통신공학부) ;
  • 정동화 (순천대학교 공과대학 정보통신공학부)
  • Published : 2004.07.14

Abstract

This paper is proposed adaptive fuzzy-neural network controller(NFC) for speed control of surface permanent magnet synchronous motor(SPMSM) drive. The design of this algorithm based on NFC that is implemented using fuzzy control and neural network. This controller uses fuzzy rule as training patterns of a neural network. Also, this controller uses the back-propagation method to adjust the weights between the neurons of neural network in order to minimize the error between the command output and actual output. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive NFC is evaluated by analysis for various operating conditions. The results of analysis prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.

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