Dr. Božidar Bratina, univ. dipl. inž., doc. Dr. Nenad Muškinja, univ. dipl. inž., Milan Rotovnik, izr. prof. dr. Marjan Golob, univ. dipl. inž. Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko

Ventil 31 (2025) 3 / Review articles / Scientific Article – 1.01

Abstract:

The paper presents implementation of advanced algorithms in PLC using the higher-level programming language SCL for PID parameter tuning in process automation. Nowadays advanced algorithms can also be implemented directly in PLCs, whereas implementation of artificial intelligence and machine learning algorithms is particularly interesting. In scope of the master thesis and student projects we implemented several advanced algorithms in PLCs and compared them with theoretical methods and practical industry tools. In the study case we implemented differential evolution algorithm optimization algorithm in the process industry control scheme for PID parameter tuning into PLC for task of airflow control. Due to the specificity and limitations of programming languages, the solutions were partially developed using tools of generative artificial intelligence, to evaluate the quality of obtained solutions. Generative models such as chatGPT, Copilot, Gemini, DeepSeek, etc., also have an impact on the teaching part, bringing new opportunities for teaching content at all levels of education. Experience through various student projects by students of automation and robotics shows that AI tools are not yet able to provide comprehensive solutions, but they can serve as good support.

Keywords:
process automation, control algorithms, PID parameter optimization, education, artificial intelligence tools

Copyright (c) 2025 Božidar Bratina, Nenad Muškinja, Milan Rotovnik, Marjan Golob

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