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Chapter

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Title

Adaptive neural speed controller for direct drive with PMSM

Authors

[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ P ] employee

Year of publication

2016

Chapter type

paper

Publication language

english

Abstract

EN The paper presents selected properties of the adaptive speed neural controller trained online for direct drive during mechanical changes of the object parameters. In the article was compared different algorithms for learning neural networks such as: backpropagation algorithm BP, momentum backpropagation MBP, Quickprop and RPROP. The authors proposed an effective method of supervision of learning neural network, which does not lead to its overfitting. The algorithms were implemented on a laboratory stand.

Pages (from - to)

1144 - 1149

DOI

10.1109/EPEPEMC.2016.7752156

URL

https://ieeexplore.ieee.org/document/7752156

Book

Proceedings of the 2016 IEEE International Power Electronics and Motion Control Conference (PEMC), Bulgaria, Varna, 25-30.09.2016

Presented on

17th International Conference on Power Electronics and Motion Control (PEMC), 25-30.09.2016, Varna, Bulgaria

Publication indexed in

WoS (15)

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