| 基于BP神经网络的开关磁阻电动机非线性建模 |
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| 引用本文： | 蔡燕 许镇琳 高超. 基于BP神经网络的开关磁阻电动机非线性建模[J]. 天津大学学报(自然科学与工程技术版), 2005, 38(10): 869-873 |
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| 作者姓名： | 蔡燕 许镇琳 高超 |
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| 作者单位： | [1]天津大学电气与自动化工程学院,天津300072 [2]天津工业大学计算机技术与自动化学院,天津300160 [3]中纺机电研究所,北京100025 |
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| 基金项目： | 国家高技术研究发展计划“863”课题（2005AA501430）. |
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| 摘 要： | 为提高开关磁阻电动机（SRM）调速系统性能，在测取准确磁特性样本数据基础上，利用神经网络所具有的非线性映射能力，基于Levenberg-Marquardt算法的BP神经网络建立了SRM的非线性模型。该模型训练收敛快，泛化能力强，且网络规模小，便于实时控制，经与样机实测数据比较，验证了该模型的准确性，将所建模型与准线性模型对比，显示出神经网络模型优越。
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| 关 键 词： | 开关磁阻电动机 非线性模型 BP神经网络 Levenberg-Marquardt算法 |
| 文章编号： | 0493-2137（2005）10-0869-05 |
| 收稿时间： | 2004-05-24 |
| 修稿时间： | 2004-05-242004-09-08 |
Building of a Nonlinear Model of Switched Reluctance Motor by BP Neural Networks |
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| CAI Yan, XU Zhen-lin, GAO Chao. Building of a Nonlinear Model of Switched Reluctance Motor by BP Neural Networks[J]. Journal of Tianjin University(Science and Technology), 2005, 38(10): 869-873 |
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| Authors: | CAI Yan XU Zhen-lin GAO Chao |
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| Affiliation: | 1. School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China ; 2. School of Computer and Automation, Tianjin Polytechnic University, Tianjin 300160, China; 3. China Textile Electrical and Mechanical Engineering Research Institute, Beijing 100025, China |
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| Abstract: | An accurate flux-linkage model of switched reluctance motor ( SRM ) is the key to improving performance of switched reluctance driving system. After measuring the accurate flux-linkage data, the nonlinear model of SRM was developed, which made use of nonlinear mapping ability of BP neural network based on Levenberg-Marquardt arithmetic. This network model is of fast training convergence, generalization and small network scale handy for real-time control. Accu(?)acy of this model was proved by experimental results. Compared with quasi-linear model, the nonlinear mode(?) performs better. |
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| Keywords: | switched reluctance motor nonlinear model back propagation neural networks Levenberg-Marquardt arithmetic |
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