Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

A Data Sharing Scheme among Industrial Process Controllers Based on UDP

Authors
Liu Liu, Jun Du, Yandong Zhang, Guanjun Qin
Corresponding Author
Liu Liu
Available Online June 2017.
DOI
10.2991/caai-17.2017.96How to use a DOI?
Keywords
industrial process controller; data sharing; user datagram protocol; object linking and embedding for process control
Abstract

With the development of industrial process control, more and more data need to be exchanged among industrial process controllers. Based on analysis of advantages & shortcomings of existing data sharing schemes among industrial process controllers, a new high-efficiency scheme is provided in this paper. Compared to other schemes, the network load is reduced and system reliability is enhanced, and the configuration is simpler. Moreover, dual network mechanism is designed to minimize data packet loss, and UDP is adopted to resend lost data while broadcasting the next message. Repeated messages can be identified and discarded. This scheme has been applied in various projects and proven effective.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
10.2991/caai-17.2017.96How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liu Liu
AU  - Jun Du
AU  - Yandong Zhang
AU  - Guanjun Qin
PY  - 2017/06
DA  - 2017/06
TI  - A Data Sharing Scheme among Industrial Process Controllers Based on UDP
BT  - Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 425
EP  - 428
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.96
DO  - 10.2991/caai-17.2017.96
ID  - Liu2017/06
ER  -