Real-time simulation of applying model predictive control on an industrial evaporation process

Abstract

A wide range of processes in chemical industry are characterized by the existence of nonlinear, multivariable interacting, time delay, and constraints properties. The evaporation process in urea industry is considered one of these processes and represents a challenge for the traditional control strategy. Model predictive control (MPC) is the most efficient advanced process control (APC) and has been extensively used in industry. MPC provides the best solution to improve the control performance for optimum process operation. This paper presents the dynamic modeling, identification and real-time simulation of urea evaporation process control in a fertilizer plant using MPC technology. The results showed a significant improvement of the control performance using MPC compared to the traditional control strategy especially during the plant load variation.