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| Format: | Recurso digital |
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| Publié: |
Zenodo
2026
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| Accès en ligne: | https://doi.org/10.5281/zenodo.18266852 |
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Table des matières:
- <p>The digital economy has intensified the complexity of technical objects and increased the demand for intelligent,<br>adaptive, and data-driven control systems. Traditional control design approaches are often insufficient to address<br>uncertainty, dynamic environments, and real-time decision-making requirements. This study investigates the development<br>of interactive modeling methods for the synthesis of intelligent control systems for technical objects operating in digital<br>economic conditions. The research evaluates how interactive modeling influences system adaptability, control accuracy,<br>development efficiency, and decision-making quality. A mixed-methods research design was applied, involving simulation<br>experiments, expert evaluations, and performance analysis of intelligent control systems. Quantitative results demonstrated<br>a 30% improvement in control accuracy and a 35% reduction in system development time. Qualitative findings revealed<br>enhanced system transparency, improved designer interaction, and higher robustness of control strategies. The study<br>highlights the importance of combining interactive modeling, intelligent algorithms, and data-driven synthesis methods to<br>improve the effectiveness of control systems in the digital economy.</p>