Abstract
A novel online-modeling scheme for the switched reluctance motor (SRM) using a B-spline neural network (BSNN) is proposed in this paper. A 2-D BSNN is designed to learn the nonlinear-flux-linkage characteristic of an SRM online and in real-time. Torque, incremental inductance, and back-emf estimates can be derived from the BSNN after training. The scheme does not require a priori knowledge of the SRM electromagnetic characteristics. Simulation and experimental results show that the scheme has a good estimation performance and robustness at low to medium motor speed.
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