The project is devoted to the development of a promising scientific direction-the theory and practice of cyber-physical systems (CFS), considered as a new information technology paradigm that combines the main trends in the development of end-to-end information and information-applied technologies.
The project develops an approach to the construction of the CFS as a "deeply integrated" technological platform that combines a group of "breakthrough" technologies-intellectualization, hierarchical network self-organization, self-learning and development, the synergetic effect of combining which gives control systems new functionality in solving a wide class of applied problems, in particular, the problems of managing poorly formalized objects, processes, phenomena under uncertainty. As one of such applied tasks in the project the problem of management of a class of industrial systems in the conditions of uncertainty of factors of influence on origin and development of the fast – developing non-standard-pre-emergency and emergency situations demanding fast acceptance of operational control decisions by criteria of multipurpose (multi-criteria) optimization is solved.
One of the important principles of the proposed approach to the formation of the concept of CFS in the project is the concept of cognitive constructivism, which explains the mechanisms and determines the possibility of implementing a management strategy in uncertainty on the basis of knowledge (for example, classes of scenarios of emergency situations, the interaction of agents, the rules of self-learning, etc.). The principle of cognitive constructivism in the theory of management as a management based on knowledge is considered to be key in the formation of cognitive processes of extraction and formation of ontological structures by constructing special cognitive models.
The practical result of the project should be the application of the principles and models of the technological platform for solving a class of problems of industrial automation and control associated with the management of difficult to formalize processes and phenomena, which also includes early detection, recognition, forecasting and adoption of operational optimal control decisions in conditions of significant uncertainty.
The first task is to develop concepts and principles of CFS as an integrated technology platform, focused on solving current technical challenges - integration of cyber-physical systems, principles of network-centric, intelligent, industrial Internet of things and Industry 4.0 into a single technological platform, forming a new type of information-management environment that solves a large class of problems of industrial automation and control under conditions of significant uncertainty.
In this regard, the first step is the formation of a General scheme of the CFS (in the form of system, functional and algorithmic models), the Assembly of individual blocks already worked out over the previous period, which can be integrated into the General concept of the CFS.
Next, common algorithms for interaction of individual elements of the common system will be created, protocols and requirements for their interaction will be developed. The development is carried out on the example of solving the problem of early detection, recognition, forecasting of development and making operational management decisions to prevent emergency situations.
It is also necessary to select and configure hardware and software functionality for working out and testing algorithms and models, in the most General form implementing the principles of intellectualization, network organization, machine learning and knowledge accumulation. The existing experience allows us to hope for the possibility of creating a software package that integrates heterogeneous models.
The next step is to develop and test mathematical software that implements CFS models and algorithms as well. Testing of RAC models and algorithms on GS of CPSC equipment.
Next comes the development of hardware and software solutions of CFS in the class of applied problems and testing on model examples, as a result of which there should be an educational and scientific laboratory complex "Cyberphysical systems of industrial automation and control"for testing industrial solutions of predictive diagnostics, automation and process control systems.
The project also includes the development of a complex of laboratories with stands for testing and demonstration of elements of innovative industrial technologies for certain industry applications: mechanical engineering, chemical production, energy.
1. Dmitri Kostenko, Dmitriy Arseniev, Vadim Onufriev and Vyacheslav Shkodyrev Solving multicriteria optimization problem for an oil refinery plant. Communications in Computer and Information Science (2019, принята к публикации)
2. Vladislav Kovalevsky and Vadim Onufriev. Hierarchical multi-agent system for production control using KPI reconciliation. Communications in Computer and Information Science (2019, принята к публикации)
3. Vladimir Khokhlovsky, Vitaly Oleynikov, Dmitry Kostenko, Vadim Onufriev, Vyacheslav Potekhin.(2019). Modernisation of a Production Process Using Multicriteria Optimisation Logic and Augmented Reality, Proceedings of the 30th DAAAM International Symposium (2019, принята к публикации)
4. Branko Katalinič, Dmitry Andreevich Kostenko, Vadim Alexandrovich Onufriev, Vyacheslav Vital'evich Potekhin. Сyber-Physical Systems in Complex Technologies and Process Control. International Conference Cyber-Physical Systems and Control (2019, принята к публикации)
5. Dmitry Andreevich Kostenko, Dmitry Germanovich Arseniev, Vadim Alexandrovich Onufriev. Distributed Knowledge Base of Intellectual Control in Smart Grids. International Conference Cyber-Physical Systems and Control (2019, принята к публикации)
6. Ковалевский В.Э., Онуфриев В.А. Мультиагентные алгоритмы согласования ключевых показателей эффективности предприятия // Научно-технические ведомости СПбГПУ. Информатика. Телекоммуникации. Управление. 2019. Т. 12, № 3. С. 67–80. DOI: 10.18721/JCSTCS.12306
7. Костенко Д.А., Онуфриев В.А., Шкодырев В.П. Многокритериальная оптимизация ректификационного процесса по алгоритму SPEA2 // Научно-технические ведомости СПбГПУ. Информатика. Телекоммуникации. Управление. 2019. Т. 12, № 2, С. 39-49. DOI: 10.18721/JCSTCS.12204
8. Distributed Ledger Technology and Cyber-Physical Systems. Multi-agent Systems. Concepts and Trends Arsenjev, D., Baskakov, D., Shkodyrev, V., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 11620 LNCS, с. 618-630, 2019 (Scopus)
9. D A Tarkhov and G F Malykhina (2019) Neural network modelling methods for creating digital twins of real objects Published under license by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1236, Number 1, 2019 J. Phys.: Conf. Ser. 1236 012056 DOI https://iopscience.iop.org/article/10.1088 /1742-6596/1236/1/012056 (Scopus)
10. The approach to emergency situation prediction in dynamical systems using neural networks, Shkodyrev, V.P., Yagafarov, K.I, ACM International Conference Proceeding Series 2018-February, с. 27-32 (Scopus) https://dl.acm.org/citation.cfm?doid=3185066.3185085
11. Knowledge based control of energy installations under uncertain conditions, Khokhlovskiy, V.N., Potekhin, V.V., Shkodyrev, V.P., Annals of DAAAM and Proceedings of the International DAAAM Symposium 29(1), с. 0582-0586, 2018 (Scopus) https://www.daaam.info/Downloads/Pdfs/proceedings/proceedings_2018/084.pdf
12. Kuleshov, S.V., A. Zaytseva, A. & Aksenov, A.Y. 2018, "The conceptual view of unmanned aerial vehicle implementation as a mobile communication node of active data transmission network", International Journal of Intelligent Unmanned Systems, vol. 6, no. 4, pp. 174-183. doi:10.1108/IJIUS-04-2018-001010.1108/IJIUS-04-2018-0010 (SJR 0,268)
13. Malykhina, G. F. Tarkhov, D. A. (2018). Digital Twin Technology as a Basis of the Industry in Future. 18-th PCSF 2018 Professional Culture of the Specialist of the Future. The European Proceedings on Social & Behavioral Sciences. Future Academy EPSBS. vol LI, 45, 416-428. DOI https://dx.doi.org/10.15405/epsbs.2018.12.02.45 (Web of Science)
14. Kostenko, D.; Kudryashov, N.; Maystrishin, M.; Onufriev, V.; Potekhin, V.; Vasiliev, V. (2018). Digital twin applications: diagnostics, optimisation and prediction, Proceedings of the 29th DAAAM International Symposium, pp.0574-0581, B. Katalinic (Ed.), Published by DAAAM International, ISBN 978- 3-902734-11-2, ISSN 1726-9679, Vienna, Austria. DOI: 10.2507/29th.daaam.proceedings.083
15. Онуфриев В.А. Управление группой автономных роботов с использованием полярных координат // Научно-технические ведомости СПбГПУ. Информатика. Телекоммуникации. Управление. 2018. Т. 10, № 4. С. 97–106. DOI: 10.18721/JCSTCS.10409
16. Onufriev, V. A. Cyber- Physical Systems Application for the Radio Telescope’s Adaptive Surface Control Task / V. A. Onufriev, A. S. Sulerova, V. V. Potekhin // Proceedings of the Automated Systems and Technologies Symposium. – 2016. – pp. 51-56
17. TECHNICAL SYSTEMS CONTROL: FROM MECHATRONICS TO CYBER-PHYSICAL SYSTEMS, Shkodyrev V.P., Studies in Systems, Decision and Control. 2016. Т. 49. С. 3-6. (Scopus, Web of Science) https://link.springer.com/chapter/10.1007%2F978-3-319-27547-5_1
18. KNOWLEDGE BASED PLANNING FRAMEWORK FOR INTELLIGENT DISTRIBUTED MANUFACTURING SYSTEMS, Fedorov A., Shkodyrev V., Zobnin S., Lecture Notes in Computer Science 2015. Т. 9141. С. 300-307. (Scopus) https://link.springer.com/chapter/10.1007%2F978-3-319-20472-7_32
19. ASPECTS OF SMART MANUFACTURING VIA AGENT-BASED APPROACH, Fedorov A., Goloschchapov E., Ipatov O., Potekhin V., Shkodyrev V., Zobnin S.,Procedia Engineering 2015. Т. 100. С. 1572-1581. (Scopus) https://www.sciencedirect.com/science/article/pii/S1877705815005573?via%3Dihub