Distributed economic model predictive control for an industrial fluid catalytic cracking unit ensuring safe operation

Abstract

The economic performance of a fluid catalytic cracking (FCC) unit plays an important role in the refinery factory. In order to improve the dynamic economic performance as well as ensure safe operation, cooperative distributed economic model predictive controls (DL-EMPCs) that optimize the product yields of the FCC unit are proposed. Discrete-time Lyapunov constraints in the MPC are designed to guarantee stability and limit the MPC output such that the decrease ratio of Lyapunov function of the closed-loop system is no less than those obtained by the designed distributed auxiliary controller. The auxiliary controller is structural and designed based on a multi-model approximation of the plant due to the strong non-linearity of the FCC unit, which can keep the system’s convergence despite the unmeasurable disturbance and the model mismatch. The feasibility and stability of the proposed DL-EMPCs are discussed as well. The proposed algorithm was applied to an industrial FCC unit model based on a refinery factory in Jiujiang, China. The results show that better economic benefits are achieved compared to the set-point regulating MPC when no disturbance occurs. Additionally, the robust performance is verified that the unit with the controller can be manipulated in a safe region even if the disturbances exist.