A new approach to design a control system for a FGR furnace using the combination of the CFD and linear system identification techniques

A new approach to design control systems for an industrial furnace with flue gas recirculation (FGR) is presented. To facilitate the control system design, a linear dynamic model is needed for the furnace. Full-scale computational fluid dynamics (CFD) simulations are used to generate the required small signal input and output data sets. Subsequently, a least squares based system identification technique is used to obtained the linear dynamic models. After model validation, feedback controller is designed based on these linear dynamic models. Finally, the performance of the designed closed-loop control system is also evaluated using both linear dynamic model and full-scale nonlinear CFD model. The comparison shows that the control system designed using the proposed approach can minimize the deviation of nitric oxides (NO) emission from the design point by minimize the dynamic NO formation, hence to prevent any excessive NO formation in the combustion process when the system subjects to disturbances.