Abstract
This study addresses the challenges associated with constructing mathematical models for systems described by imprecise or fuzzy data inputs and outputs. A novel approach is introduced for synthesizing linguistic models tailored to complex technical systems operating within fuzzy environments. Specifically, the methodology is applied to the modeling of delayed coking unit (DCU) reactors using fuzzy logic principles. A fuzzy inference system was designed based on expert-derived rule bases to evaluate coke quality and fugacity under uncertain operational conditions. MATLAB’s Fuzzy Logic Toolbox was employed to simulate the fuzzy environment and derive the models. The developed linguistic models effectively capture the influence of temperature and pressure on coke quality, offering a powerful tool for system analysis and decision-making.