Advanced Control of MEA-Based CO2 Capture Systems

Post-combustion CO2 capture using monoethanolamine (MEA) is a mature mitigation technology, yet its high energy demand and complex dynamics remain major challenges. This study presents a unified dynamic modeling and control framework for an MEA-based absorption–regeneration system, focusing on a comparative evaluation of PID, fuzzy logic control (FLC), and model predictive control (MPC) under realistic operating disturbances. A control-oriented surrogate model was developed in MATLAB R2024b/Simulink and validated against published benchmark trends. The control objective was to maintain CO2 capture efficiency above 90% while minimizing reboiler energy consumption under ±10% inlet CO2 concentration and flue gas flow disturbances. Simulation results showed that PID control ensures basic stability but exhibits slow recovery and high energy usage, while FLC improves robustness with limited dynamic improvement. MPC consistently maintained capture efficiency above the target value, reduced the settling time by approximately 37%, and achieved a 12.4% reduction in average reboiler duty compared to PID control. The results demonstrate that a unified, implementation-oriented modeling framework enables the effective assessment of advanced control strategies and supports the energy-efficient operation of industrial MEA-based CO2 capture systems.

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