Fluid catalytic cracking unit control using model predictive control and adaptive neuro fuzzy inference system: Comparative study

The disrupted energy markets, growing environmental regulations and economic downtrend have driven the oil and gas industry to search for more efficient strategies to control its facilities. Fluid Catalytic Cracking (FCC) has kept its key role between processes of oil refineries due to its contribution in refinery's overall performance and impact on economic profitability. Multiple control techniques have been studied to control the unit, as it presents a very strong challenge for control theory because of its complexity. This work compares Model Predictive Control (MPC); one of the most successful control technologies in industry to Adaptive Neuro Fuzzy Inference Systems (ANFIS) controller, as a candidate of the artificial intelligence control techniques.