| 开关磁阻电机的模糊神经网络模型 |
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| 引用本文： | 李大芃,王守臣,诸静. 开关磁阻电机的模糊神经网络模型[J]. 中国电机工程学报, 2000, 20(1): 11-14 |
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| 作者姓名： | 李大芃 王守臣 诸静 |
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| 作者单位： | 浙江大学电机系,浙江省,杭州市,310027 |
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| 摘 要： | 首次给出了开关磁阻电机的模糊神经网络模型，基于模糊神经结构上的特点，提出了一和中ＢＰ算法和最小二乘的混合算法，仿真结果表明模糊神经网络模型有比Ｓｉｇｍｏｉｄ神经网络模型更高的精度和更快的收敛速度。
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| 关 键 词： | 模糊神经网络 开关磁阻电机 建模 BP算法 |
| 文章编号： | 0258-8013 (2000) 01-0011-04 |
| 修稿时间： | 1999-01-18 |
THE FUZZY NEURAL NETWORKS MODEL OF SWITCHED RELUCTANCE DRIVERS |
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| LI Da-peng,WANG Shou-chen,ZHU Jing. THE FUZZY NEURAL NETWORKS MODEL OF SWITCHED RELUCTANCE DRIVERS[J]. Proceedings of the CSEE, 2000, 20(1): 11-14 |
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| Authors: | LI Da-peng WANG Shou-chen ZHU Jing |
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| Abstract: | This article presents the fuzzy neural networks(FNN) model of nonlinear switched reluctance drivers for the first time. Based on the characteristics of FNN architecture we propose a hybrid learning rule combining the gradient method and the least squares estimator. Simulation results show that the FNN model is more precise and less time consuming for convergence than the Sigmoid neural networks model. |
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| Keywords: | fuzzy neural networks switched reluctance deriver modeling |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
