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http://dx.doi.org/10.5302/J.ICROS.2007.13.5.429

On-line Parameter Estimation of IPMSM Drive using Neural Network  

Choi, Jung-Sik (순천대학교 전기제어공학과)
Ko, Jae-Sub (순천대학교 전기제어공학과)
Chung, Dong-Hwa (순천대학교 전기제어공학과)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.13, no.5, 2007 , pp. 429-433 More about this Journal
Abstract
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 ststor resistance in IPMSM Drives. 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 is confirmed by the operating characteristics controlled by neural networks control.
Keywords
IPMSM; neural network; parameter change; torque ripple minimization; parameter estimator;
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