LAUSR

Abstract This work presents the procedure used for the identification of the dynamic model of a 50 MW petrochemical furnace. This real system is responsible for the generation of thermal energy, necessary for the heating of the load currents of the processing unit of bituminous shale derivatives. The variability or instability of temperature control, airflow for combustion and fuel flow, may affect the results related to the efficiency of the petrochemical furnace. In addition to the financial losses, another relevant aspect is the impact on the environment, i.e., it is a variable that must be maintained within operational restrictions. Based on the problems highlighted, it is justifiable to invest in multivariable predictive control. For this reason, the identification and validation of the model is essential to the success of the performance of the predictive controller algorithm. In this work, all the steps to obtain the model of the multivariable process of the petrochemical furnace are presented. The model obtained was validated by analysis of computational methods and tools. The result of the validations shows that the identified model reflects with great accuracy the behavior of the actual plant, in this case the petrochemical furnace.