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Overview of implementation principles of artificial intelligence methods in industrial control systems Cover

Overview of implementation principles of artificial intelligence methods in industrial control systems

Open Access
|Feb 2025

References

  1. L. Körösi, V. Németh, J. Paulusová and Š. Kozák, “RBF neural network for identification and control using PAC”, International Joint Conference SOCO’13-CISIS’13-ICEUTE’13, Salamanca, Spain, Berlin : Springer, pp. 329-337, 2013.
  2. L. Körösi, J. Paulusová and Š. Kozák, “PLC online control using orthogonal neural network”, MENDEL 2013 : 19th International Conference on Soft Computing, Brno, Czech Republic, pp. 227-232, 2013
  3. L. Körösi, “Neural Network Modeling and Control Using Programmable Logic Controller”, Posterus, Vol. 4, No. 12, 2011.
  4. L. Körösi, S. Kajan, J. Paulusová and P. Štefaňák, “Servo System Control Using Gestures”, 2022 Cybernetics & Informatics (K&I) 31st IEEE International Conference, Visegrád, Hungary, p. 5, 2022.
  5. C. Tian, J. Yi and J. Gao, “An Intelligent Stereo Garage System,”, 2024 43rd Chinese Control Conference (CCC), pp. 6439–6444, 2024.
  6. M. Akhmetov, D. Kanymkulov, A. Amirov, A. Askhatova and T. Alizadeh, “Integrated Machine Vision and PLC Commanding for Efficient Bottle Label Detection in Industrial Processes: A Unified Approach for Quality Control”, 2024 10th International Conference on Control, Automation and Robotics (ICCAR), pp. 66–70, 2024.
  7. G. A. David, P. M. d. C. Monson, C. Soares, P. d. O. Conceição, P. R. de Aguiar and A. Simeone, “IoT-Driven Deep Learning for Enhanced Industrial Production Forecasting”, IEEE Internet of Things Journal, pp. 1–1, 2024.
  8. J. Liguš, T. A. Murajda and S. Filip, “Optimisation of hybrid power system with on site meteo station with integrated prediction methods”, 8th International Hybrid Power Plants & Systems Workshop (HYB2024), vol. 2024, pp. 273–279, 2024.
  9. A. Alihodžić, A. Mujezinović and E. Turajlić, “Artificial neural network-based method for overhead lines magnetic flux density estimation”, Journal of Electrical Engineering, vol. 75, no. 3, pp. 181–191, 2024.
  10. D. Filimonov, A. Onabek, K. Smolyarchuk and T. Alizadeh, “Integrating Computer Vision in a CODESYS PLC to Enable Intelligent Object Identification,”, 2024 9th International Conference on Mechatronics Engineering (ICOM), pp. 65–70, 2024.
  11. V. Kurilová, S. Rajcsányi, Z. Rábeková, J. Pavlovičová, M. Oravec and N. Majtánová, “Detecting glaucoma from fundus images using ensemble learning”, Journal of Electrical Engineering, vol. 74, no. 4, pp. 328–335, 2023.
  12. L. Wen, B. Liang, L. Zhang, B. Hao and Z. Yang, “Research on Coal Volume Detection and Energy-Saving Optimization Intelligent Control Method of Belt Conveyor Based on Laser and Binocular Visual Fusion”, IEEE Access, vol. 12, pp. 75238-75248, 2024.
  13. E. Genc, M. E. Yildirim and Y. B. Salman, “Human activity recognition with fine-tuned cnn-lstm”, Journal of Electrical Engineering, vol. 75, no. 1, pp. 8–13, 2024.
  14. W. Cao, “Research on Control Optimization Method of Grinding System Based on PLC and Swarm Intelligence Algorithm”, 2023 7th Asian Conference on Artificial Intelligence Technology (ACAIT), pp. 1014–1018, 2023.
  15. C.-T. Lin, M.-F. Han, Y.-Y. Lin, S.-H. Liao and J.-Y. Chang, “Neuro-fuzzy system design using differential evolution with local information”, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), pp. 1003–1006, 2011.
  16. F. Zúbek, A. Melichar, I. Kenický, L. Körösi and I. Sekaj, “Autonomous Systems Control Design Using Neuro-Evolution”, 2022 Cybernetics & Informatics (K&I), pp. 1–6, 2022.
  17. Schneider Electric, “Ecostruxure control expert - program languages and structure reference manual”, https://download.schneider-electric.com/files?p_Doc_Ref=35006144K01000&p_enDocType=User+guide&p_File_Name=35006144_K01_000_25.pdf, Last accessed: November 2024.
  18. H. Berger, Automating with simatic: Controllers, software, programming, data, Publicis, 5th edition, 2013.
  19. H. Berger, Automating with simatic s7-1500: Configuring, programming and testing with step 7 professional, Publicis, 2nd edition, 2014.
  20. F. D. Petruzella, Programmable Logic Controllers, McGraw-Hill Education, 5th edition, 2016.
  21. J. Hugh, Automating Manufacturing Systems with PLCs, Lulu.com, 5th edition, 2008.
  22. B. G. Lipták, Instrument Engineers’ Handbook, Vol. 2: Process Control and Optimization, CRC Press, 4th edition, 2005.
  23. L. A. Bryan and E. A. Bryan, Programmable Controllers - Theory and Implementation, Amer Technical Pub, 2nd edition, 2003.
  24. W. Bolton, Programmable Logic Controllers, Newnes, 5th edition, 2009.
  25. Siemens, “Library of general functions (lgf) for simatic step 7 (tia portal) and simatic s7-1200 / s7-1500”, https://support.industry.siemens.com/cs/document/109479728/library-of-general-functions-(lgf)-for-simatic-step-7-(tia-portal)-and-simatic-s7-1200-s7-1500?dti=0lc=en-SK, 2024. Last accessed: November 2024.
  26. J. Cai and Z. Deng, “Offline and online modeling of switched reluctance motor based on rbf neural networks”, Journal of Electrical Engineering, vol. 64, no. 3, pp. 186–190, 2013.
DOI: https://doi.org/10.2478/jee-2025-0010 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 99 - 105
Submitted on: Nov 12, 2024
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Published on: Feb 13, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2025 Ladislav Körösi, Slavomír Kajan, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.