An Intelligent Control Framework for Industrial Boilers Using IoT and Self-Tuning PID

Abstract

The Internet of Things (IoT)-enabled Adaptive PID controller discussed in this study is designed to enhance the safety and performance of industrial boilers. Due to the complex, nonlinear, and time-varying behavior of boiler systems and their high sensitivity to disturbances, conventional PID controllers often suffer from poor stability, degraded tracking performance, and increased fuel consumption. To overcome these limitations, the proposed methodology integrates adaptive control algorithms with IoT-based real-time monitoring to enable online tuning of controller parameters. Key process variables such as temperature, pressure, and water level are measured using sensors and interfaced through an ESP32 microprocessor, providing continuous feedback for control-gain optimization and sustained system stability. The system also supports intelligent automation and predictive maintenance, contributing to reduced operational costs and improved reliability. Experimental validation demonstrates significant improvements in system stability, energy efficiency, and response time when compared with traditional PID control approaches. Overall, the proposed IoT-enabled adaptive control framework offers a practical and cost-effective solution for modern industrial boiler management, aligned with the objectives of Industry 4.0.