CONTROL SYSTEMS: TRADITIONAL AND MODERN APPROACHES

Аннотация

This research explores the distinctions and synergies between traditional and modern
control systems, emphasizing their respective roles in advancing industrial practices. The study
examines traditional systems, such as proportional-integral-derivative (PID) controllers, which
provide robust solutions based on feedback loops but face adaptability challenges in dynamic
environments. Conversely, modern control approaches leveraging neural networks and multi-agent
architectures are highlighted for their ability to enhance autonomous decision-making and fault
detection. Furthermore, the transition toward state-space representation and nonlinear control is
discussed as a means to capture multi-variable interactions more effectively than classical methods.
The findings suggest that harmonizing traditional reliability with modern, adaptive technologies is
essential for the evolution of Industry 4.0 and resilient infrastructure. Ultimately, the convergence of
these approaches offers a comprehensive strategy for operational optimization across diverse sectors.