JACoW is a publisher in Geneva, Switzerland that publishes the proceedings of accelerator conferences held around the world by an international collaboration of editors.
@inproceedings{patil:icalepcs2023-tupdp102,
author = {A. Patil and D. Daniel and F. Ghawash and K. Kaufmann and C. Kern and B. Schofield and A.S. Sündermann and F. Varela},
% author = {A. Patil and D. Daniel and F. Ghawash and K. Kaufmann and C. Kern and B. Schofield and others},
% author = {A. Patil and others},
title = {{Leveraging Local Intelligence to Industrial Control Systems through Edge Technologies}},
% booktitle = {Proc. ICALEPCS'23},
booktitle = {Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'23)},
eventdate = {2023-10-09/2023-10-13},
pages = {793--798},
paper = {TUPDP102},
language = {english},
keywords = {controls, PLC, operation, software, interface},
venue = {Cape Town, South Africa},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {19},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {02},
year = {2024},
issn = {2226-0358},
isbn = {978-3-95450-238-7},
doi = {10.18429/JACoW-ICALEPCS2023-TUPDP102},
url = {https://jacow.org/icalepcs2023/papers/tupdp102.pdf},
abstract = {{Industrial processes often use advanced control algorithms such as Model Predictive Control (MPC) and Machine Learning (ML) to improve performance and efficiency. However, deploying these algorithms can be challenging, particularly when they require significant computational resources and involve complex communication protocols between different control system components. To address these challenges, we showcase an approach leveraging industrial edge technologies to deploy such algorithms. An edge device is a compact and powerful computing device placed at the network’s edge, close to the process control. It executes the algorithms without extensive communication with other control system components, thus reducing latency and load on the central control system. We also employ an analytics function platform to manage the life cycle of the algorithms, including modifications and replacements, without disrupting the industrial process. Furthermore, we demonstrate a use case where an MPC algorithm is run on an edge device to control a Heating, Ventilation, and Air Conditioning (HVAC) system. An edge device running the algorithm can analyze data from temperature sensors, perform complex calculations, and adjust the operation of the HVAC system accordingly. In summary, our approach of utilizing edge technologies enables us to overcome the limitations of traditional approaches to deploying advanced control algorithms in industrial settings, providing more intelligent and efficient control of industrial processes. }},
}