The study aims to develop a system of models and a method for optimizing the operating modes of a catalytic reforming unit using fuzzy information, which makes it possible to effectively control the reforming process of the object under study. The object of study of this work is a catalytic reforming unit that has been operating for more than half a century and is characterized by the lack of clarity of some part of the initial information. The research methods are methods of system analysis, mathematical modeling, multicriteria optimization, and expert assessments, as well as methods of theories of fuzzy set theories, which allows formalizing and using fuzzy information, as well as experimental-statistical methods. As a result of the conducted research, the following main results were obtained. Based on a systematic approach, an effective methodology has been developed for developing a system of models of interconnected plant units using various types of available information, including fuzzy information. Using the proposed method, hybrid models have been developed to determine the volume of the produced catalyzate and its quality indicators. A scheme has been constructed for combining the developed models of the main units of the catalytic reforming unit into a single package of models. The built system of models makes it possible to systematically simulate the operation of the plant under study and improve the efficiency of the facility by increasing the volume of target products produced and improving its quality indicators. A statement of the problem of multicriteria optimization is obtained, taking into account the partial fuzziness of the initial information, and a heuristic method for its solution is developed, which is based on the use of knowledge, experience, and intuition of the decision-maker. The results of modeling and optimization show the effectiveness of the proposed fuzzy approach.

Technological objects and processes are often characterized by fuzzy initial information necessary for developing their models and optimization. The purpose of the study is to develop a method for synthesizing linguistic models of fuzzy described objects and a heuristic method for solving the multicriteria optimization problem in a fuzzy environment. Based on the expert assessments and logical rules of conditional inference, a method for synthesizing linguistic models was developed for describing processes with fuzzy input and output parameters. To solve the problem of multicriteria optimization, a heuristic method based on the modification and combination of various optimality principles is proposed. Coking reactor models were developed by modifying the successive regression inclusion method and the least squares method. Linguistic models of the delayed coking process were developed in the Fuzzy Logic Toolbox, allowing to evaluate the coke quality depending on the temperature and pressure of coking reactors. Using the proposed heuristic method, the problem of two-criteria optimization of the delayed coking process with fuzzy constraints is solved. The results confirm the advantages of the proposed fuzzy approach compared with the well-known approaches. Unlike them, the proposed method allows making adequate decisions in a fuzzy environment by maximizing the use of available fuzzy information.

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.

Many technological systems are characterized by fuzzy initial information, necessary for the development of their models, optimization and control of operating modes. Therefore, the purpose of this study is to formulate decision making problems for optimizing and controlling operating modes of such systems in a fuzzy environment and to develop methods for solving them. The developed heuristic methods of fuzzy multi-criteria decision making are based on the modification and combination of different principles of optimality. The proposed methods based on system models, knowledge and experience of the decision maker allow iterative improvement and effective decision making. On the basis of experimental–statistical methods, methods of expert evaluation, statistical and fuzzy models of the stabilization column have been developed. The conditions for judging the fuzzy model’s effectiveness are determined and investigated. Using the proposed heuristic method based on the main criterion and maximin, the problem of two-criterion optimization of the stabilization column parameters in a fuzzy environment is solved. The results obtained confirm the advantages of the proposed method of fuzzy decision making in comparison with the results of known methods. The developed heuristic methods differ from known ones because they allow making adequate decisions in a fuzzy environment by maximizing the use of the collected fuzzy information.

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.

The relevance of the research is caused by the need to solve effectively the problems of controlling the operating modes of chemical-technological systems, which are multi-criteria, characterized by the uncertainty and fuzziness of the initial information. Since real chemical-technological systems in production are multi-criteria and often work in the conditions of unclear initial information, formalization and effective solution of such problems in a fuzzy environment is very important and relevant for science and production. The main aim of the research is to develop a method for constructing mathematical models of chemical-technological systems based on available information of various kinds (theoretical, statistical, expert, fuzzy information); get multicriteria optimization problem statement to control such systems and develop a heuristic approach to its solution; also, to test the results obtained in practice for construction of mathematical models of chemical-technological system for benzene production and the control modes of its operation in a fuzzy environment. Objects: complex chemical-technological systems with the example of a technological plant for production of benzene, which are described by a vector of criteria and characterized by unclear initial information. Methods: methods of system analysis and fuzzy sets theories, methods of mathematical modeling and multi-criteria choice, experimental statistical methods for developing mathematical models. Results. The authors have proposed the method for developing mathematical models of chemical-technological systems based on available information of various types, including initial fuzzy information. The new tasks of control of the chemical technological systems in the conditions of fuzziness of the initial information obtained by modifications of various compromise schemes for working in a fuzzy environment. The tasks of multicriteria optimization in controlling technological system are reduced to multicriteria problems of fuzzy mathematical programming and based on modifying the principles of maximin and Pareto optimality, heuristic algorithm for solving the formulated problem of optimal control is developed. These results are realized in practice in constructing mathematical models of the main aggregates of the chemical-technological system for production of benzene and in setting and solving the task of controlling the operating modes of this system in a fuzzy environment. Analysis and comparison of the obtained results allow drawing a conclusion about the effectiveness of the proposed approach to solving control problems on the basis of models in conditions of indistinct initial information.