A hybrid method is proposed for the development of a structured set (complex) of mathematical models for a complicated chemical engineering system (CES) of an oil refinery in ambiguous conditions...

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.

This research develops a method for synthesizing linguistic models of fuzzy systems with fuzzy input and output parameters that are described by linguistic variables. Based on the proposed method, linguistic models of the Title 1000 catalytic cracking unit for heavy residues at the Shymkent oil refinery are developed, describing the dependence of the volume and quality of gasoline on the input and operating parameters of the facility, which are fuzzy. It is substantiated that the use of a fuzzy approach, which allows the use of the experience, knowledge, and intuition (intelligence) of the decision maker and subject matter experts, is the most suitable effective method for synthesizing models of complex, fuzzily described objects and processes for comparison with other methods. The main idea of the proposed work is to solve the problems of shortage and fuzziness of initial information when developing models and optimizing the operating modes of a catalytic cracking unit through the use of knowledge, experience, and intuition of experts in this field. To solve the problems of the shortage of initial quantitative information and the fuzziness of available information when developing mathematical models, it is proposed to systematically use statistical methods, expert assessment methods, and a heuristic method based on fuzzy logic. The scientific novelty of the research lies in the development of a method for synthesizing linguistic models in a fuzzy environment and an algorithm for its implementation, which makes it possible to describe the dependence of the fuzzy values of the object’s output parameters on its fuzzy input and operating parameters. The proposed approach allows the formalization and synthesis of models of fuzzily described objects when other methods of model development are not applicable or do not give the expected results. The results of the work were simulated in the MATLAB Fuzzy Logic Toolbox.

Mathematical equations for the multi-criteria task of the optimisation of chemical engineering systems, for example for the optimisation of working regimes for industrial installations for benzene production, have been formulated and developed, and based on fuzzy mathematical methods, algorithms for their solution have been developed. Since the chemical engineering system, which is being researched, is characterised by multiple criteria and often functions in conditions of uncertainty, the presenting problem is formulated in the form of multi-criteria equations for fuzzy mathematical programming. New mathematical formulations for the problems being solved in a fuzzy environment and heuristic algorithms for their solution have been developed by the modification of various optimisation principles based on fuzzy mathematical methods.

This article is devoted to the study of decision-making problems of hydrotreating process control in the production of high-quality gasoline under conditions of scarcity and fuzziness of the initial information, ultimately developing an approach to solve them. A systematic method is proposed that makes it possible to develop a package of mathematical models of a complex of interconnected units of chemical-technological systems based on available information of various types. Using the proposed system method, a package of models of the main interconnected units in which the hydrotreating process took place was developed. A decision-making problem was formulated to control the hydrotreating process in a fuzzy environment based on the developed system of models. By modifying the Pareto principle of optimality for fuzzy conditions, a heuristic method for solving the given decision-making problem was developed to control the hydrotreating process in a fuzzy environment. The novelty of the proposed heuristic method lies in the full use of the collected fuzzy information, which represents the knowledge, intuition and experience of the decision makers and experts. Accordingly, the proposed heuristic decision-making method makes it possible to achieve a high adequacy and efficiency of decisions made when solving production problems in a fuzzy environment. The results obtained were applied in practice to solve decision-making problems for hydrotreating process control at the Atyrau refinery. The results obtained show the advantages of the proposed heuristic method for solving decision-making problems of hydrotreating process control over known methods.

The relevance of the study is substantiated by the fact that when managing the processes of oil transportation through main pipelines, it becomes necessary to determine and select the optimal operating modes of the oil pipeline units, taking into account the fuzziness of some part of the initial information. In this regard, solving the problem of multi-criteria selection of effective operating modes for an oil heating station for a hot oil pipeline system, which is often described in a fuzzy environment, based on the apparatus of fuzzy set theories, is an urgent scientific and practical problem. A method for the synthesis of models in the conditions of fuzzy output parameters of the object has been developed, with the help of which fuzzy models of the investigated oil heating station of the main oil pipeline have been built. Based on the modification and combination of various optimality principles, mathematical formulations of the problem of multi-criteria selection of effective operating modes for an oil heating station in a fuzzy environment are obtained. By modifying and adapting the principles of guaranteed results and equality in a fuzzy environment, a heuristic method has been developed for solving the formulated problem of selecting object's operation modes using the initial fuzzy information. The proposed heuristic method for multi-criteria selection in a fuzzy environment is based on the use of the experience and knowledge of the decision-maker. The proposed approach is implemented in the formulation and solution of the problem of multi-criteria selection of operating modes of the oil heating station in Atyrau of the Uzen-Atyrau-Samara main oil pipeline. As a result of the application of the proposed method, an improvement in the degree of fulfillment of a fuzzy restriction on environmental impact was achieved by 2 %, as well as the optimal values of the operating parameters of the object were improved: the temperature was reduced by 1.85 % (5.67 K), pressure – by 0.04 % (kPa) and fuel consumption – by 2.9 % (0.0002 kg/s). The obtained results have confirmed the effectiveness of the proposed approach to solving the assigned tasks.