Reduced-Order Modeling and Control of Heat-Integrated Air Separation Column Based on Nonlinear Wave Theory

Abstract

The process of low-temperature air separation consumes a significant amount of energy. Internal heat-integrated distillation technology has considerable energy-saving potential. Therefore, the combination of low-temperature air separation and heat-integrated distillation technology has led to the development of a heat-integrated air separation column (HIASC). Due to the heat integration and the inherent complexity of air separation, the modeling and control of this process poses significant challenges. This paper first introduces the nonlinear wave theory into the HIASC, derives the expression for the velocity of the concentration distribution curve movement and the curve describing function, and then establishes a nonlinear wave model. Compared to the traditional mechanical models, this approach greatly reduces the number of differential equations and variables while ensuring an accurate description of the system characteristics. Subsequently, based on the wave model, a model predictive control scheme is designed for the HIASC. This scheme is compared with two conventional control schemes: PID and a general model control. The simulation results demonstrate that MPC outperforms the other control schemes from the response curves and performance metrics.