Training artificial neural networks for the implementation of the Petri nets synthesis process
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2026.2.11Keywords:
artificial neural networks, logical control algorithms, hybrid system, automatic synthesis of Petri nets, training methodAbstract
The important task has been solved in this scientific research related to specific development and verification of the fundamental suitability of the method for automatic synthesis of Petri nets based on the functioning of an artificial neural network. This allows to automate the generating process of logical control algorithms. It has been proposed to divide the artificial neural network into separate local networks for the subsequent stepwise training. Such stepwise training is necessary to form the logical control algorithm and to synthesize the appropriate Petri net. The proposed principles can be applied in the early stages of training for an artificial neural network while synthesizing a Petri net. It has been conducted the experiments linked to the training of local neural networks and to implement the formation of an algorithm for logical control of the laboratory machine for processing chemical solutions. As a result of the experiment, it has been determined the fundamental suitability for the stepwise training method of neural networks for generating Petri nets and the automated formation of logical control algorithms.
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