INTELLIGENT CONTROL METHODS FOR BIOREACTORS: APPLICATION OF FUZZY LOGIC RULES IN WASTEWATER TREATMENT

Abstract

This paper examines the application of fuzzy logic rules as an intelligent control approach to enhance the efficiency of bioreactors used in wastewater treatment. The bioreactors under consideration are employed for wastewater purification. Traditional control approaches often face challenges due to the nonlinear, dynamic, and uncertain nature of biological processes. In comparison with conventional strategies, fuzzy logic provides a flexible and robust framework for modeling such systems, while allowing the integration of expert knowledge and linguistic rules. In this study, a fuzzy rule-based control system was developed to regulate key operational parameters of a wastewater bioreactor. Simulation results demonstrate that the fuzzy logic–based controller improves system stability, reduces deviations from optimal operating conditions, and enhances treatment efficiency compared to traditional methods. The findings confirm that fuzzy logic–based control strategies represent a reliable and adaptive tool for optimizing processes in bioreactors within modern wastewater treatment systems. Furthermore, the proposed approach shows strong potential for real-time applications, particularly in environments where precise mathematical models are difficult to obtain. The integration of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) may further strengthen the accuracy of predictions and adaptability to changing conditions. These results highlight the importance of intelligent control techniques in advancing sustainable wastewater management and open pathways for future experimental validation and large-scale implementation.