Methods for Developing Models in a Fuzzy Environment of Reactor and Hydrotreating Furnace of a Catalytic Reforming Unit
| Autor: | Ainur Zhumadillayeva, Kulman Orazbayeva, Sandugash Iskakova, B. B. Orazbayev, Lyailya Kurmangaziyeva, Kanagat Dyussekeyev |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Computer science QH301-705.5 QC1-999 hydrotreating reactor Least squares Fuzzy logic catalytic reforming hydrogen-containing gas linguistic models General Materials Science Biology (General) MATLAB Process engineering Instrumentation QD1-999 computer.programming_language Fluid Flow and Transfer Processes Mathematical model Basis (linear algebra) business.industry Process Chemistry and Technology Physics General Engineering Process (computing) Experimental data hydrotreating furnaces Engineering (General). Civil engineering (General) Computer Science Applications Chemistry fuzzy models hydrogenate TA1-2040 business computer Nonlinear regression |
| Zdroj: | Applied Sciences, Vol 11, Iss 8317, p 8317 (2021) Applied Sciences Volume 11 Issue 18 |
| ISSN: | 2076-3417 |
| Popis: | Methods for the development of fuzzy and linguistic models of technological objects, which are characterized by the fuzzy output parameters and linguistic values of the input and output parameters of the object are proposed. The hydrotreating unit of the catalytic reforming unit was investigated and described. On the basis of experimental and statistical data and fuzzy information from experts and using the proposed methods, mathematical models of a hydrotreating reactor and a hydrotreating furnace were developed. To determine the volume of production from the outlet of the reactor and furnace, nonlinear regression models were built, and fuzzy models were developed in the form of fuzzy regression equations to determine the quality indicators of the hydrotreating unit—the hydrogenated product. To identify the structure of the models, the ideas of sequential inclusion regressors are used, and for parametric identification, a modified method of least squares is used, adapted to work in a fuzzy environment. To determine the optimal temperature of the hydrotreating process on the basis of expert information and logical rules of conditional conclusions, rule bases are built. The constructed rule bases for determining the optimal temperature of the hydrotreating process depending on the thermal stability of the feedstock and the pressure in the hydrotreating furnace are implemented using the Fuzzy Logic Toolbox application of the MatLab package. Comparison results of data obtained with the known models, developed models and real, experimental data from the hydrotreating unit of the reforming unit are presented and the effectiveness of the proposed approach to modeling is shown. |
| Databáze: | OpenAIRE |
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