Персона: Толоконский, Андрей Олегович
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Analysis of Using of Neural Networks for Real-Time Process Control
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Machine learning is one of the key technologies of the current scientific and technological revolution. Despite the fact that research in the field of “intelligent” control systems began in the last century, real-time control systems based on machine learning, specifically neural networks, began to be actively implemented only in the past decade. In this paper, the authors analyze the current state of the problem of using real-time control systems based on neural networks and using machine learning in real-time control systems.
Application of Machine Learning for Solving Problems of Nuclear Power Plant Operation
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.Nowadays, the industry is actively introducing technologies based on machine learning: predictive analytics, computer vision, industrial robots, etc. In this article authors discuss the possible application of machine learning to improve the operation of nuclear power plant (NPP) power units: diagnostics of the state of equipment (both technological equipment of normal operation systems and equipment of safety systems); definition of irrelevant alarm; determination of the state of the reactor plant; application of machine learning in equipment control algorithms. The report also examines the existing difficulties in introducing machine learning into NPP operation: issues of stability of control systems based on machine learning; the issue of interpretability of solutions issued by systems based on machine learning; small data set size for training machine learning models.
Concept of instrumentation of digital twins of nuclear power plants units as observers for digital NPP I&C system
© 2019 IOP Publishing Ltd.The relevance of the idea under consideration lies in the development of the use of digital twins of power units in the nuclear industry. With their help, we can not only predict the state of technological equipment, etc., but also solve the problem of parameter tuning of automatic regulators in different operating modes of NPP unit. Authors consider approaches to this problem based on optimal control theory, fuzzy logic and machine learning. Advantages and disadvantages of each approach are considered.