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백정우(Jeong-Woo Baek),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),강성준(Sung-Jun Kang),장미금(Mi-Geum Jang),문주희(Ju-Hui Mun),정동화(Dong-Hwa Chung) 전력전자학회 2010 전력전자학술대회 논문집 Vol.2010 No.7
This paper proposes maximum torque control of IPMSM drive using optimal current. This control method is applicable over the entire speed range which 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 id for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi-MFC and ANN controller. Also, this paper proposes maximum control of IPMSM drive using approximation method. This method is decreased the burden of digital signal process(DSP) in calculation of optimal current. This paper proposes the analysis results to verify the effectiveness of the MFC and ANN controller. Also it verifies the validity of maximum torque control of IPMSM drive with optimal current.
백정우(Jeong-Woo Baek),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),강성준(Sung-Jun Kang),장미금(Mi-Geum Jang),문주희(Ju-Hui Mun),정동화(Dong-Hwa Chung) 대한전기학회 2010 대한전기학회 학술대회 논문집 Vol.2010 No.4
This paper proposes maximum torque control of IPMSM drive using multi model reference adaptive fuzzy controller(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which 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 id for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi-MFC and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes maximum control of IPMSM drive using approximation method. This method is decreased the burden of digital signal process(DSP) in calculation of optimal current. This paper proposes the analysis results to verify the effectiveness of the MFC and ANN controller. Also it verifies the validity of maximum torque control of IPMSM drive with approximation method.
AFLC를 이용한 IPMS 드라이브의 NN 파라미터 추정
백정우(Jeong-Woo Baek),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),강성준(Sung-Jun Kang),장미금(Mi-Geum Jang),문주희(Ju-Hui Mun),정동화(Dong-Hwa Chung) 대한전기학회 2010 대한전기학회 학술대회 논문집 Vol.2010 No.7
A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance and adaptive fuzzy learning controller(AFLC) for speed control in IPMSM Drives. AFLC is changed fuzzy rule base by rule base modifier for robust control of IPMSM. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator and AFLC is confirmed by compare to conventional algorithm.
다중 MFC에 의한 IPMSM 드라이브의 MTPA 제어
백정우(Jeong-Woo Baek),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),강성준(Sung-Jun Kang),장미금(Mi-Geum Jang),문주희(Ju-Hui Mun),정동화(Dong-Hwa Chung) 한국조명·전기설비학회 2010 한국조명·전기설비학회 학술대회논문집 Vol.2010 No.5월
This paper proposes maximum torque control of IPMSM drive using multi model reference adaptive fuzzy controller(MFC) and artificial neural network(ANN). This control method is applicable over the entire speed range which 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<SUB>d</SUB> for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi-MFC and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed and current control of IPMSM using MFC and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled MFC and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the MFC and ANN controller.
백정우(Jeong-Woo Baek),고재섭(Jae-Sub Ko),최정식(Jung-Sik Choi),강성준(Sung-Jun Kang),장미금(Mi-Geum Jang),김순영(Sun-Young Kim),정동화(Dong-Hwa Chung) 대한전기학회 2009 대한전기학회 학술대회 논문집 Vol.2009 No.10
This paper proposes photovotaic/thermal (PV/T) hybrid module to get the Electrical and Thermal performance of building integrated photovoltaic(BIPV) system. BIPV system is decreased the system efficiency because output of PV is decreased by the thermal rising on generating. In order to improve the efficiency of BIPV module, water cooling system is applied and generated thermal is used the warm water system. Water cooling system uses the HBPI thermal control and flow control algorithm. Electrical and thermal performance of proposed PV/T module is confirmed through the actual experiment and proved the valid of this paper.