Prospects for the Implementation of Cyber-Physical Systems for Monitoring and Control of Microclimate in the Context of Industry 4.0

Abstract

The paper examines the prospects and prerequisites for the implementation of cyber-physical systems for monitoring and controlling the microclimate of industrial premises in the context of industrial digital transformation and the Industry 4.0 concept. It is shown that traditional automatic control systems based on PID controllers are limited in their ability to account for the nonlinearity, inertia, and multifactor nature of microclimate formation processes. The feasibility of transitioning to intelligent control systems that integrate sensor networks, computational modules, and actuators into a unified cyber-physical architecture is substantiated. A parametric mathematical model of the microclimate is presented, which formalizes the relationships between temperature, humidity, air gas composition, and actuating mechanisms while considering external disturbances. The role of neural network models of the NNARX type as the predictive core of an intelligent control system is revealed. It is demonstrated that the integration of predictive models into the structure of a cyber-physical system enables a transition from reactive to predictive control, which contributes to improving the stability of environmental parameters, reducing energy consumption, and increasing the reliability of industrial processes.