Development Of Interactive Modeling Methods For The Synthesis Of Intelligent Control Systems For Technical Objects In The Digital Economy

The digital economy has intensified the complexity of technical objects and increased the demand for intelligent,adaptive, and data-driven control systems. Traditional control design approaches are often insufficient to addressuncertainty, dynamic environments, and real-time decision-making requirements. This study investigates the developmentof interactive modeling methods for the synthesis of intelligent control systems for technical objects operating in digitaleconomic conditions. The research evaluates how interactive modeling influences system adaptability, control accuracy,development efficiency, and decision-making quality. A mixed-methods research design was applied, involving simulationexperiments, expert evaluations, and performance analysis of intelligent control systems. Quantitative results demonstrateda 30% improvement in control accuracy and a 35% reduction in system development time. Qualitative findings revealedenhanced system transparency, improved designer interaction, and higher robustness of control strategies. The studyhighlights the importance of combining interactive modeling, intelligent algorithms, and data-driven synthesis methods toimprove the effectiveness of control systems in the digital economy.