Analysis of the features of modeling controlled systems using cognitive maps

In modern engineering, the development of effective management strategies for complex technical facilities requires the integration of qualitative and quantitative parameters. Traditional mathematical models are not always suitable for systems with a high degree of uncertainty, complex relationships, and vague expertise. Cognitive maps are a promising tool for formalizing knowledge and modeling system behavior depending on various factors. The purpose of the article is to develop an approach to constructing cognitive maps of a controlled technical system based on simulation data using fuzzy logic to determine the weighting coefficients of relationships between concepts. An algorithm for constructing a cognitive map based on the analysis of quantitative simulation data is proposed. The algorithm includes the stages of defining concepts, conducting simulation modeling, collecting data, determining the relationships between concepts, and calculating weighting coefficients using fuzzy logic. The use of fuzzy logic made it possible to formalize the relationship between concepts, taking into account uncertainty. An example of constructing a cognitive map for the injection molding machine temperature control system is considered. The results can be used to solve cognitive modeling problems, technical systems management problems, and uncertainty-based decision support system development problems.