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HAI 제어기에 의한 유도전동기 드라이브의 고성능 제어
南守明(Su-Myeong Nam),高在涉(Jae-Sub Ko),崔正植(Jung-Sik Choi),鄭東和(Dong-Hwa Chung) 대한전기학회 2006 전기학회논문지 D Vol.55 No.4
This paper is proposed hybrid artificial intelligent(HAI) controller for high performance of induction motor drive. The design of this algorithm based on fuzzy-neural network(FNN) controller 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 FNN controller is evaluated by analysis for various operating conditions. The results of experiment prove that the proposed control system has strong high performance and robustness to parameter variation, and steady-state accuracy and transient response.
ANN과 FMRLC를 이용한 유도전동기의 센서리스 속도제어
남수명(Su-Myeong Nam),이정철(Jung-Chul Lee),이홍균(Hong-Gyun Lee),이영실(Young-Sil Lee),박병상(Bung-Sang Park),정동화(Dong-Hwa Chung) 전력전자학회 2004 전력전자학술대회 논문집 Vol.- No.-
Artificial intelligence control that use Fuzzy, Neural network, genetic algorithm etc. in the speed control of induction motor recently is studied much. Also, sensors such as Encoder and Resolver are used to receive the speed of induction motor and information of position. However, this control method or sensor use receives much effects in urroundings environment change and react sensitively to parameter change of electric motor and control Performance drops. Presume the speed and position of induction motor by ANN in this treatise, and because using FMRLC that is consisted of two Fuzzy Logic, can correct Fuzzy Rule Base through learning and save good response special quality in change of condition such as change of parameter.
LM-FNN 제어기에 의한 IPMSM 드라이브의 속도 추정 및 제어
남수명(Su-Myeong Nam),이홍균(Hong-Gyun Lee),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),정동화(Dong-Hwa Chung) 전력전자학회 2005 전력전자학술대회 논문집 Vol.- No.-
This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using learning mechanism-fuzzy neural network(LM-FNN) and artificial neural network (ANN) control. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control