Model Predictive Control of a Catalytic Flow Reversal Reactor with Heat Extraction

This paper presents the formulation of a controller for a Catalytic Flow Reversal Reactor (CFRR) with heat extraction. The controller is based on the Model Predictive Control (MPC) concept. The MPC scheme uses a model that assumes plug flow and neglects radial gradients in the reactor but accounts for the two phases within the reactor. The prediction of the future output behavior from the model is obtained by using the Method of Characteristics as proposed by Shang et al. (2004) for convection dominated distributed parameter systems. The formulated controller is applied to a CFRR unit for the catalytic oxidation of fugitive lean methane mixtures. The objective of the control algorithm is to maintain stable reactor operation, while extracting the maximum amount of useful energy by hot gas removal from the mid-section of the reactor. Simulations are used to show the performance of the designed controller.