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浏览/检索结果: 共4条，第1-4条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序作者升序作者降序提交时间升序提交时间降序题名升序题名降序 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] 收藏  |  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 收藏  |  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. 收藏  |  浏览/下载：12/0  |  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.