Open Cognitive Control System Architecture
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
In recent years, the automation industry is moving towards Industry 4.0 and cyber-physical systems. There is an increasing demand for smarter plants and plant modules. In this paper, we are proposing an architecture for the open cognitive control system. This will provide the benefits of a control strategy based on the data analysis. With the possibility to connect with the cloud, this will enable easy updates and exchange of task modules that would ensure the system to keep up with the technological advancements. This will also improve the accuracy and lifetime of the automation system. To meet the requirements of flexibility, speed and reliability of the system, the architecture has been based on distributed and concurrent systems design. A detailed description of the architecture along with its challenges have been presented in this paper. A comparison of different implementation techniques for certain blocks has also been discussed.
Details
Original language | English |
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Title of host publication | 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) |
Publisher | IEEE |
Pages | 1673-1677 |
Number of pages | 5 |
ISBN (print) | 978-1-7281-0304-4 |
Publication status | Published - 13 Sept 2019 |
Peer-reviewed | Yes |
Conference
Title | 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation |
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Abbreviated title | ETFA 2019 |
Conference number | 24 |
Duration | 10 - 13 September 2019 |
Degree of recognition | International event |
Location | University of Zaragoza |
City | Zaragoza |
Country | Spain |
External IDs
Scopus | 85074202607 |
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ORCID | /0000-0001-5165-4459/work/146166743 |
ORCID | /0009-0008-7719-8293/work/146166803 |
Keywords
Keywords
- Cognitive control, Control systems, Process industry, Real-time systems, Automation, Process control, Embedded Systems