The book examines the high energy consumption of refrigeration systems in the food industry, with a particular focus on the Ecuadorian context. The research was conducted in a company located in Valle Hermoso parish, Santo Domingo canton, Santo Domingo de los Tsáchilas province, Ecuador; the company’s name is kept confidential. Challenges were identified related to high energy costs, thermal fluctuations, and premature equipment wear, resulting from the absence of advanced control systems in the refrigeration chambers. The work integrates theoretical and practical foundations on automatic control and mathematical modeling of critical variables such as temperature, humidity, pressure, and airflow, as well as the application of intelligent control strategies, including PID, predictive (MPC), adaptive, and neural controllers. Simulation models were developed in Simulink to evaluate system dynamics and validate closed-loop responses under different conditions. Results showed that neural controllers applied to temperature achieved a stable response with a 7.99% overshoot and a settling time of 378.12 seconds, while the adaptive controller for humidity reached optimal performance with 0% overshoot and 65.39 seconds settling time. Variables such as pressure and airflow also showed significant improvement under adaptive control, demonstrating stability and rapid adjustment. This book represents an academic and technical contribution for students, researchers, and professionals in control, automation, and energy efficiency, illustrating how intelligent control techniques can optimize industrial refrigeration systems, reduce energy consumption, improve environmental sustainability, and ensure the quality of food products.

This book is included in DOAB.