电工技术学报2009，Vol.24Issue(8)：46-51,64,7.
开关磁阻电机的Pi-sigma模糊神经网络建模
Modeling of Switched Reluctance Motor Based on Pi-Sigma Fuzzy Neural Network
摘要
Abstract
The high saturation of magnetic circuit and the doubly salient structure of switched reluctance motor (SRM) make the flux linkage a nonlinear function of rotor position and phase current. In this paper, the pi-sigma fuzzy neural network, which has the merit of T-S type fuzzy logic and neural network, is adopted to develop the nonlinear model of SRM and an adaptive learning rate training algorithm with momentum is applied. Relatively high precision model of SRM is implemented. It has simple structure, less training epoch and fast online calculation. The sampled phase current and rotor position are non-equally spaced. Thus a reasonable distribution of measured data is reached. The precision and generalization ability of the model are improved. Meanwhile the number of measured data is reduced. Compared with the measured data and generalization validate data, the output data of the model are in good agreement with those data. This proves that the precision of the model developed in this paper is relatively high. The model has the merits of relatively strong generalization ability, simple structure and fast calculation.关键词
开关磁阻电机/建模/Pi-sigma模糊神经网络/T-S模糊逻辑Key words
Switched reluctance motor/ modeling/ Pi-sigma fuzzy neural network/ T-S type fuzzy logic分类
信息技术与安全科学引用本文复制引用
修杰,夏长亮,王世宇..开关磁阻电机的Pi-sigma模糊神经网络建模[J].电工技术学报,2009,24(8):46-51,64,7.基金项目
国家自然科学基金(50705062)、国家重点基础研究发展计划(2009CB219700)和天津市自然科学基金(06YFJMJC01900)资助项目. （50705062）
