Перегляд за автором "Jabrayilzade, E."

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  • Зображення мініатюри
    Публікація
    Application of the Fuzzy Sets Theory in the Management of Technological Processes for the Production of Automation Technical Means
    (2025) Omarov, M.; Bilousov, M.; Starodubtsev, M.; Shybanov, S.; Jabrayilzade, E.
    It is established that the main problems of algorithmization for the management of technological processes under conditions of uncertainty are the high dimensionality of the task, the need for prompt identification of technological objects of control and the choice of optimal control influences. It is shown that these problems can be solved using fuzzy logic and decision theory. A method for formalizing fuzzy concepts based on an objective probabilistic approach is proposed, which increases the reliability of modeling results. Based on fuzzy logic, a method for identifying multidimensional technological objects has been developed, in which, in order to reduce the dimensionality of the problem, a conjunctive inference rule is used instead of the generally accepted disjunctive one to build a relationship between a multidimensional input and output, which simplifies the inference procedure and leads to a more compact and convenient model for practical application.
  • Зображення мініатюри
    Публікація
    Study of a Hybrid Mobile Manipulating Robot Control System Based on Machine Vision and Sensor Networks in Industry 5.0 Production Scenarios
    (NGO «European Scientific Platform», 2025) Nevliudov, I. Sh.; Yevsieiev, V.; Jabrayilzade, E.
    In the current conditions of transition to the Industry 5.0 paradigm, the key task is to ensure effective and safe interaction between humans and robots in a shared production environment. Mobile manipulator robots perform complex operations in a dynamically changing environment where numerous factors influence the control system's decisions: people's movement trajectories, the presence of obstacles, changes in the location of objects, etc. Traditional control systems based solely on sensor data or machine vision have limitations in response speed and recognition accuracy. The use of a hybrid control system that combines machine vision and sensor networks makes it possible to improve the accuracy of situation assessment, decision-making speed, and the safety of interaction with the operator.