Abstract
The least square support vector machine (LS-SVM) inductance model optimized by the particle swarm optimization (PSO) algorithm is presented for bearingless switched reluctance motor (BSRM). The training sample is first obtained using the 3D finite element model (FEM) of the prototype, and then LS-SVM model is built, whose hyper-parameters are optimized using PSO algorithm. The absolute error and relative error are computed, which demonstrate the high accuracy of the proposed model.
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