Comparison of three control strategies for optimization of spray dryer operation. (September 2017)

• Record Type: Journal Article
• Authors: Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik; Utzen, Christer; Jørgensen, John Bagterp
• Is Part Of: Journal of process control. Volume 57(2017)
• Page Start: 1
• Page End: 14
• Publication Date: 2017-09
• Subjects: Spray drying -- Real-time optimization -- Model predictive control -- Economic model predictive control -- PI control; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2017.05.008
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: Optimization and control of the operation of a simulated four-stage spray dryer. Model predictive control with real-time optimization (MPC-RTO). Economic nonlinear model predictive control (E-NMPC). MPC-RTO and E-NMPC improves the profit of operation with more than 8.5% compared to the industrially used PI control strategy. Abstract: Spray drying is the preferred process to reduce the water content of many chemicals, pharmaceuticals, and foodstuffs. A significant amount of energy is used in spray drying to remove water and produce a free flowing powder product. In this paper, we present and compare the performance of three controllers for operation of a four-stage spray dryer. The three controllers are a proportional-integral (PI) controller that is used in industrial practice for spray dryer operation, a linear model predictive controller with real-time optimization (MPC with RTO, MPC-RTO), and an economically optimizing nonlinear model predictive controller (E-NMPC). The MPC with RTO is based on the same linear state space model in the MPC and the RTO layer. The E-NMPC consists of a single optimization layer that uses a nonlinear system of ordinary differential equations for its predictions. The PI control strategy has a fixed target that is independent of the disturbances, while the MPC-RTO and the E-NMPC adapt the operating point to the disturbances. The goal of spray dryer operation is to optimize the profit of operation in the presence of feed composition and ambient air humidity variations; i.e. to maximize the production rate, while minimizing the energy consumption, keeping the residual moisture content of the powder below a maximum limit, and avoiding that the powder sticks to the chamber walls. We use an industrially recorded disturbance scenario in order to produce realistic simulations and conclusions. The key performance indicators such as the profit of operation, the product flow rate, the specific energy consumption, the energy efficiency, and the residual moisture content of the produced powder are computed and compared for the three controllers. In this simulation study, we find that the economic performance of the MPC with RTO as well as the E-NMPC is considerably improved compared to the PI control strategy used in industrial practice. The MPC with RTO improves the profit of operation by 8.61%, and the E-NMPC improves the profit of operation by 9.66%. The energy efficiency is improved by 6.21% and 5.51%, respectively.