|4/2011 - 4|
PID Neural Network Based Speed Control of Asynchronous Motor using Programmable Logic ControllerMARABA, V. A. , KUZUCUOGLU, A. E.
|Click to see author's profile on SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (431 KB) | Citation | Downloads: 1,902 | Views: 4,630|
control, neural network, PID, PIDNN, PLC
control(12), neural(6), system(5), networks(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 23 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04004
Web of Science Accession Number: 000297764500004
SCOPUS ID: 84856594182
This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC) was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.
Web of Science® Times Cited: 6 [View]
View record in Web of Science® [View]
View Related Records® [View]
SCOPUS® Times Cited: 7
View record in SCOPUS® [Free preview]
 Decentralized PID neural network control for a quadrotor helicopter subjected to wind disturbance, Chen, Yan-min, He, Yong-ling, Zhou, Min-feng, Journal of Central South University, ISSN 2095-2899, Issue 1, Volume 22, 2015.
Digital Object Identifier: 10.1007/s11771-015-2507-9 [CrossRef]
 Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules, Zhang, Zhen, Ma, Cheng, Zhu, Rong, Sensors, ISSN 1424-8220, Issue 12, Volume 16, 2016.
Digital Object Identifier: 10.3390/s16101709 [CrossRef]
 A Novel Method for Inverter Faults Detection and Diagnosis in PMSM Drives of HEVs based on Discrete Wavelet Transform, AKTAS, M., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 12, 2012.
Digital Object Identifier: 10.4316/AECE.2012.04005 [CrossRef] [Full text]
 A solution for study of positioning control of two axes, Rata, Mihai, Rata, Gabriela, 2016 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-5090-6129-7, 2016.
Digital Object Identifier: 10.1109/ICEPE.2016.7781419 [CrossRef]
 A solution for the study and understanding of PID controllers, Rata, Mihai, Rata, Gabriela, Chatziathanasiou, Vasilis, 2014 International Conference and Exposition on Electrical and Power Engineering (EPE), ISBN 978-1-4799-5849-8, 2014.
Digital Object Identifier: 10.1109/ICEPE.2014.6969893 [CrossRef]
 A solution for study of PID controllers using cRIO system, Rata, Gabriela, Rata, Mihai, 2015 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE), ISBN 978-1-4799-7514-3, 2015.
Digital Object Identifier: 10.1109/ATEE.2015.7133685 [CrossRef]
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.