Optimization design of the bearingless switched reluctance motor based on SVM and GA
Proceedings of the 30th Chinese Control Conference, CCC 2011（2011）
摘要
The optimization design method of the bearingless switched reluctance motor is presented. This paper mainly aims at nonlinear regression modeling of the bearingless switched reluctance motor with support vector machines, which is based on the finite element method simulating, and parameter optimization of the bearingless switched reluctance motor is based on genetic algorithms. The results prove that the nonparametric model has good precision. More important, the optimized motor can produce rated torque and has the maximum suspension force of every unit of rotor. © 2011 Chinese Assoc of Automation.
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关键词
bearingless switched reluctance motor,genetic algorithms optimization,nonparametric modeling,optimization design,support vector machine,finite element method,regression analysis,support vector machines,genetic algorithm,optimal design,nonlinear regression,optimization,finite element analysis,frequency modulation,switched reluctance motor,finite element methods,switches,genetic algorithms,rotor,svm
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