引用本文: | 孙炜, 翟晓华, 张路金, 王耀南.一种自组织小波神经网络定子电阻估计器[J].控制理论与应用,2007,24(3):371~373.[点击复制] |
SUN Wei, ZHAI Xiao-hua, ZHANG Lu-jin, WANG Yao-nan.Stator resistance estimator based on self-organization wavelet neural network[J].Control Theory and Technology,2007,24(3):371~373.[点击复制] |
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一种自组织小波神经网络定子电阻估计器 |
Stator resistance estimator based on self-organization wavelet neural network |
摘要点击 1699 全文点击 2391 投稿时间:2005-07-10 修订日期:2006-02-23 |
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DOI编号 10.7641/j.issn.1000-8152.2007.3.008 |
2007,24(3):371-373 |
中文关键词 直接转矩控制 小波 神经网络 自组织 |
英文关键词 direct torque control wavelet neural network self-organization |
基金项目 湖南省自然科学基金资助项目(06JJ50121) |
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中文摘要 |
定子电阻的准确估计是改善直接转矩控制低速性能的关键技术. 为了提高定子电阻的在线估计精度和速度, 本文将小波分析、自组织算法和神经网络技术相结合, 提出了一种自组织小波神经网络定子电阻估计器. 该网络继承了小波分析优异的局部特性和神经网络的自学习能力, 具有较高的估计精度. 并采用自组织算法对小波元的数量进行了离线优化, 大大简化了网络结构, 提高了在线估计的实时性. |
英文摘要 |
Exact estimation of stator resistance is the key technology to improve the low speed performance of direct torque control. To improve the accuracy and speed of on-line stator resistance estimation, a self-organization wavelet neural network estimator is proposed in this paper by combining wavelet analysis, self-organization algorithm and neural network technology together. The proposed network inherits the excellent local performance of wavelet analysis and the self-learning ability of neural network to get high estimation accuracy, and its wavelet number is optimized off-line by using self-organization algorithm to simplify the network structure and improve the on-line estimation speed. |
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