High-performance current control for switched reluctance motors based on on-line estimated parameters

To reduce torque ripple in a switched reluctance motor (SRM) by current profiling, a high-performance current controller is necessary. This study presents a high-performance current controller for SRM drives. A B-spline neural network is used to model the non-linearity of the SRM and estimate back electromotive force (EMF) and incremental inductance on-line in real time. The on-line modelling scheme does not require a priori knowledge of the machine's electromagnetic characteristics. Based on the on-line estimated parameters, a current controller with adjustable PI gains and back-EMF decoupling is implemented. The performance of the current controller has been demonstrated in simulation and experimentally using a four-phase 8/6 550'W SRM drive system.

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