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이홍균(Hong-Gyun Lee),이정철(Jung-Chul Lee),정택기(Tack-Gi Jung),정동화(Dong-Hwa Chung) 전력전자학회 2002 전력전자학술대회 논문집 Vol.- No.-
This paper investigates the adaptive control of a fuzzy logic based speed and flux controller for a vector controlled induction motor drive 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 model reference adaptive control(MRAC) fuzzy controller is evaluated by simulation for various operating conditions The validity of the proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system
ANN-PE에 의한 IPMSM 드라이브의 센서리스 제어
이홍균(Hong-Gyun Lee),이정철(Jung-Chul Lee),이영실(Young-Sil Lee),남수명(Su-Myeong Nam),김종관(Jong-Gwan Kim),박병상(Bung-Sang Park),정동화(Dong-Hwa Chung) 전력전자학회 2004 전력전자학술대회 논문집 Vol.- No.-
Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using adaptive neural network. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network-parameter estimator(ANN-PE) controller. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the hybrid intelligent control and ANN-PE
퍼지-신경회로망 제어기를 이용한 유도전동기의 최대토크 제어
이홍균(Hong-Gyun Lee),남수명(Su-Myeong Nam),최정식(Jung-Sik Choi),고재섭(Jae-Sub Ko),정동화(Dong-Hwa Chung) 전력전자학회 2005 전력전자학술대회 논문집 Vol.- No.-
In this paper, we propose fuzzy-neural network controller that combines a fuzzy control and the Neural Networks for high performance control of induction motor drive. Also, this paper is proposed control of maximum torque per ampere of induction motor. This strategy is proposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using fuzzy-neural network controller is verified by simulation at dynamic operation conditions.
MRAS-NN을 이용한 IPMSM 드라이브의 속도와 위치 추정
이홍균(Hong-Gyun Lee),이정철(Jung-Chul Lee),정택기(Taek-Gi Jung),이영실(Young-Sil Lee),정동화(Dong-Hwa Chung) 전력전자학회 2003 전력전자학술대회 논문집 Vol.2003 No.11
This paper combines the adaption of MRAS with the ability of NN for better modeling of nonlinear system. It presents an MRAS using an NN in the adaption mechanism The technique is applied to a IPMSM drive. The torque constant and stator resistance variations on the speed and position estimations over a wide speed range has been studied. The NN estimators are able to track the varying parameter of different speeds with consistent performance. The validity of the proposed estimator is confirmed by the operating characteristics controlled by neural networks control