Post-combustion carbon capture （PCC） systems， as effective carbon reduction devices， are important for enhancing CO2 capture efficiency and reducing energy consumption. To address control issues of PCC systems， a novel composite model-free adaptive control （MFAC）method is proposed，aiming for overcoming the reliance on precise models and the difficulties in adapting to varying parameters and uncertainties encountered by traditional methods. Composite MFAC integrates an extended state observer to estimate total system disturbances， improving systems' tracking and disturbance rejection capabilities. Comparative simulations on different control methods of PCC systems were conducted. In simulations for tracking CO2 capture rate setpoints， composite MFAC demonstrated excellent tracking capability， whose acceleration time was only 95.69 s， which was 4.65 s faster than that of traditional MFAC and 78.02 s faster than that of PID control. In simulations for evaluating disturbance rejection performances， the composite MFAC exhibited the minimal deviation， smallest integral absolute error （IAE） and integral square error （ISE） among the three control methods， demonstrating a robust disturbance rejection capability. Simulation results validate the effectiveness and applicability of the proposed control approach.
