Development of ANFIS-Based Controller for Spray Drying Machine

Artificial Intelligence has significantly and drastically changed how people live and have assisted in finding innovative solutions to 21st-century issues in food production systems. In this situation, these technologies can aid in the preservation of valuable food items using spray-drying equipment. However, current control techniques, such as the PID algorithm included in these spray-drying machines, raise several concerns about how to retain high accuracy when manufacturing new native products that produce high-quality powders. These issues served as the impetus for this study on adopting an ANFIS machine learning algorithm with an aim to improve the accuracy of the current spray drying control system. Results show that the developed model did well in evaluations and that its deployment within the adaptive controller was effective. These accuracy improvements led to the development of a said adaptive controller for spray-drying machines to have an improved thermal efficiency ratio and more consistent product quality.