Neural Network Parameter Estimation of IPMSM Drive using AFLC
AFLC를 이용한 IPMSM 드라이브의 NN 파라미터 추정

Jae-Sub Ko, Jung-Sik Choi, Dong-Hwa Chung
2011 The Transactions of The Korean Institute of Electrical Engineers  
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 contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM.
more » ... he 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 comparing to conventional algorithm.
doi:10.5370/kiee.2011.60.2.293 fatcat:sf5xyj3wpfcgdksdkql7zjziui