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Due to the rotor position of switched reluctance motor (SRM) is a highly nonlinear function of stator windings current and flux linkage, so general linear and analytical methods are difficult to achieve precision results, in the paper, a method is presented that a genetic RBF neural network (RBFNN) is used to rotor position sensorless detection of SRM. Hence, extensive mapping ability of neural network...
Band selection is an important preprocessing procedure for analysis of hyperspectral data, which suffers from the vast amount of data and Hughes phenomenon. In recent years, band (feature) selection using Neural Network such as Multi-layer Forward Neural Network (MLFNN), Radial Basis Function Neural Network (RBFNN) and Double Parallel Feedforward Neural Network (DPFNN) becomes a promising method for...
This paper deals with the characteristics analysis and the normal force minimization of a synchronous permanent magnet planar motor (SPMPM) with a Halbach magnet array. The characteristics such as flux density, back-EMF and thrust are evaluated and compared with experimental values. The measured values of back-EMF are in good agreement with the simulation ones, but the experimental results of thrust...
In this paper, synchronous permanent magnet planar motor (SPMPM) with Halbach array is proposed for its high energy density. Genetic algorithm is applied to optimize the thrust of the proposed SPMPM based on six variables. The thrust is remarkably improved form 31.93[N] to 38.92[N]
In this paper, the characteristics of a novel synchronous permanent planar motor (SPMPM) are calculated firstly by analytical method. Then the force optimization is accomplished by using genetic algorithm. Finally the comparisons between the original and the optimal model are accomplished. The rationality is verified by the experiment data
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