Characteristics-based model predictive control of a catalytic flow reversal reactor

This paper describes the formulation and tuning of a model-based controller for a catalytic flow reversal reactor (CFRR). A plug flow non-linear pseudo-homogeneous mathematical representation of the process is used to model the mass and energy transport phenomena for the model-based controller. A combination of the method of characteristics and model predictive control (MPC) technology is used to formulate the controller (Shang et al., Ind. Eng. Chem. Res. 43(9) 2140-2149 (2004)). Mass extraction from the miclsection of the reactor is used as the manipulated variable. Numerical simulations are used to show the performance of the formulated controller. The performance of the controller is evaluated on a simulated catalytic flow reversal reactor unit for combustion of lean methane streams for reduction of greenhouse gases emissions.