Talk · National Conference on Electrical and Electronics Engineering · April 27, 2026

Intellectualized Decision Support System for Controlling the High-Quality Sulfur Production Process

Batyr Orazbayеv, Аinur Zhumadillayeva, Kulman Orazbayeva, Ramazan Yessirkessinov

Abstract

An approach to the development of an Intelligent Decision Support System (IDSS) for optimal control of the highquality sulfur production process under conditions of uncertainty and fuzziness is proposed. The relevance of this study is due to the complexity and nonlinearity of the sulfur production process, which is characterized by fuzziness of certain parameters and high sensitivity of sulfur quality to fluctuations in operating conditions. A hybrid method based on the systematic use of neural networks and fuzzy logic is proposed. Using this method, neuro-fuzzy models of the high-quality sulfur production process were developed, enabling effective control of the process under conditions of uncertainty and fuzziness. The structure of the IDSS is created, and its main interrelated subsystems, modules, and elements are described. The scientific novelty of this work lies in the development of an IDSS for controlling the high-quality sulfur production process based on the integration of expert knowledge and artificial intelligence methods. The practical significance is determined by the possibility of applying the proposed system in real operating conditions of sulfur production units to improve sulfur quality and enhance process stability. In addition, the use of artificial intelligence methods and expert knowledge increases the efficiency and robustness of the technological process.

Industrial Technology and Control SystemsFuzzy Logic and Control SystemsFault Detection and Control Systemsintelligent decision support systemfuzzy neural networkartificial neural networks

Intellectualized Decision Support System for Controlling the High-Quality Sulfur Production Process

Abstract

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