Nonlinear model predictive control and H∞ robust control for a post-combustion CO2 capture process

Abstract This work focuses on the design of a nonlinear model predictive controller (NMPC) and an H ∞ robust controller for an MEA-based CO 2 capture process. The model used in the NMPC is a nonlinear, additive, autoregressive model with exogenous (NAARX) inputs. Uncertainties are unavoidable in chemical processes. Therefore, a robust controller is designed for the CO 2 capture process based on μ-synthesis with a DK-iteration algorithm. The effects of uncertainties due to measurement noise and model mismatches are evaluated for both the NMPC and robust controller. The system disturbances include a number of input and output disturbances such as the flue gas flowrate and composition and variable capture targets. This study shows that the tradeoff between the fast tracking performance of the NMPC and the superior robust performance of the robust controller must be considered while designing the control system for the CO 2 capture units.