System identification and model predictive control for the optimization of a gas sweetening process

This work presents the development, simulation and evaluation of a model predictive control (MPC) for the optimization of the gas sweetening process performed in an amine plant of Maraven, SA, located in “El Tablazo” Petrochemical Complex, Venezuela. The mathematical models of the process are obtained by the application of system identification techniques. The version of MPC known as dynamic matrix control (DMC) is applied in order to regulate the contents of CO ₂ in an ethane output stream from the absorber tower using amine as a treating agent. Simulation results indicate that, with the MPC system, ethane is maintained within sweet product specifications in a precise, reliable and more profitable manner compared to conventional control techniques