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Improving PID Control Based on Neural Network
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Santiago de Querétaro, Querétaro, Mexico.
2018 (English)In: Proceedings - 2018 International Conference on Mechatronics, Electronics and Automotive Engineering, ICMEAE 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 186-191, article id 8743120Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a neural network PID controller is presented, applying neural network and reducing PID configuration in controlling industry process. Two built neural networks are considered as cores to adjust weights which result in the suggested PID parameters. Algorithm program is written in Siemens TIA Portal and tested in Factory I/O. It is verified after analysis that the proposed model has a better performance than conventional PID in terms of steady state, deviations and consistency of control value after tuning time.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 186-191, article id 8743120
Keywords [en]
neural network, PID, PLC, TIA Portal
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-36844DOI: 10.1109/ICMEAE.2018.00042Scopus ID: 2-s2.0-85068864686ISBN: 9781538691915 (print)OAI: oai:DiVA.org:miun-36844DiVA, id: diva2:1342389
Conference
2018 International Conference on Mechatronics, Electronics and Automotive Engineering, ICMEAE 2018; Cuernavaca; Mexico; 27 November 2018 through 30 November 2018
Available from: 2019-08-13 Created: 2019-08-13 Last updated: 2019-08-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • text
  • asciidoc
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