A Composite Model Predictive Control Strategy for Furnaces

作者：Zang, Hao; Li, Hongguang^*; Huang, Jingwen; Wang, Jia

来源：Chinese Journal of Chemical Engineering, 2014, 22(7): 788-794.

DOI：10.1016/j.cjche.2014.05.014

• Furnace
• Tracking nonlinear model predictive control
• Economic nonlinear model predictive control
• Distributed model predictive control

Tube furnaces are essential and primary energy intensive facilities in petrochemical plants. Operational optimization of furnaces could not only help to improve product quality but also benefit to reduce energy consumption and exhaust emission. Inspired by this idea, this paper presents a composite model predictive control (CMPC) strategy, which, taking advantage of distributed model predictive control architectures, combines tracking nonlinear model predictive control and economic nonlinear model predictive control metrics to keep process running smoothly and optimize operational conditions. The controllers connected with two kinds of communication networks are easy to organize and maintain, and stable to process interferences. A fast solution algorithm combining interior point solvers and Newton's method is accommodated to the CMPC realization, with reasonable CPU computing time and suitable online applications. Simulation for industrial case demonstrates that the proposed approach can ensure stable operations of furnaces, improve heat efficiency, and reduce the emission effectively.

• 出版日期2014-7
• 单位北京化工大学