Abstract
Abstract The structures and model parameters of the hydrotreating reactor of a catalytic reforming unit were identified based on available information of various types. The structural identification of the developed reactor models was carried out on the basis of the ideas of the sequential switching of regressors method, and the parameters were identified using the least squares method modified for working in a fuzzy environment. The developed models have the structure of nonlinear regression models (for output, i.e. hydrogenated) and fuzzy multiple regression equations (for qualitative indicators of hydrogenated). When developing the models with the source information, we used available statistical and experimental data describing the operation of the reactor and fuzzy information representing the knowledge, experience and judgment of experts about the hydrotreatment process. Based on the simulation of the hydrotreatment reactor, a graph of the temperature dependence of the hydrogenate yield of the reactor is constructed. A linguistic model has been constructed that estimates the dependence of the temperature of the hydrotreating process on the quality of the feedstock. This model allows to determine the optimal temperature value in a fuzzy environment depending on the quality of the raw material being cleaned.