Fuzzy Control of the Photocatalytic Removal of Emerging Contaminants

This project focuses on simulating the removal of emerging contaminants (ECs), such as pharmaceuticals (Triclosan and Diclofenac), through photocatalytic advanced oxidation processes. Conventional treatment methods are inefficient against these microcontaminants, which pose significant risks to health and the environment. The proposed solution involves designing and simulating a fuzzy control system, based on fuzzy logic, to model and optimize removal efficiency. The methodology includes selecting membership functions, defining fuzzy operators and rules (using the Mamdani or Sugeno inference engine), and applying fuzzification and defuzzification processes. The ultimate goal is to quantify contaminant removal through MATLAB simulation and compare these simulated results with previous experimental data obtained by other researchers to validate the control model.<br/><br/><b>Goal</b>: <br/>To simulate the photocatalytic removal of emerging contaminants, specifically Triclosan and Diclofenac, in wastewater using a fuzzy control system implemented in MATLAB.<br/><br/><b>Research lines</b>: <br/>Thermocatalytic assessment of agricultural waste