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科研机构
江苏大学 [2]
清华大学 [1]
长春光学精密机械与物... [1]
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会议论文 [3]
期刊论文 [1]
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2016 [2]
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Online Inductance Identifications of Interior Permanent Magnet Synchronous machine Based on Adaline Neural Network
会议论文
2016 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2016-01-01
作者:
Ren, Yufei[1]
;
Liu, Guohai[2]
;
Chen, Qian[3]
;
Zhou, Huawei[4]
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  |  
浏览/下载:11/0
  |  
提交时间:2019/12/24
Interior permanent magnet synchronous machine
adaline neural network
online indectance identification
Online Inductance Identifications of Interior Permanent Magnet Synchronous machine Based on Adaline Neural Network
会议论文
13th IEEE Vehicle Power and Propulsion Conference (VPPC)
作者:
Ren, Yufei[1]
;
Liu, Guohai[2]
;
Chen, Qian[3]
;
Zhou, Huawei[4]
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/24
Interior permanent magnet synchronous machine
adaline neural network
online indectance identification
Nuclide identification algorithm based on K-L transform and neural networks
期刊论文
2010, 2010
Chen, Liang
;
Wei, Yi-Xiang
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浏览/下载:6/0
An improved adaptive neural network method for control system (EI CONFERENCE)
会议论文
2006 International Conference on Machine Learning and Cybernetics, August 13, 2006 - August 16, 2006, Dalian, China
Wang L.-M.
;
Xie M.-J.
;
Wu D.-Y.
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浏览/下载:12/0
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提交时间:2013/03/25
Classical methods for designing a controller depend on the accuracy of system model. However
plant's models and other parts in a physical system can not accurately represent all possible dynamics. Thus the controller designed is usually not the optimal one. In this article
a new
simple adaptive control method
which combines the classical frequency domain method with the neural network theory
is proposed. Firstly
we can obtain a controller using classical method. Secondly we use the coefficients in digitized controller equation as the initial values of an Adaline network. Finally
LMS learning rules is used to adjust the weights adaptively. Experimental results show that this method is very effective in improving the performance of conventional controller. 2006 IEEE.
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