Monday, March 17, 2025 11:00 MLIT Room 310, Online seminar via MTS Link M. KatulinAutomatic control systems based on fuzzy logic technologies, artificial neural networks and quantum-like algorithms Abstract: The report presents the results of work on the development of intelligent automatic control systems based on artificial neural networks, fuzzy logic and quantum-like algorithms. To test technologies on real physical devices, a specialized robotics testing ground was created in LIT. Various manipulators, tracked vehicles, and other objects operating in a non-deterministic environment serve as control objects at the robotic testing ground. Software libraries have been developed that implement genetic and fuzzy controller algorithms and enable interaction between devices. The results obtained at the robotic test site were used to develop an intelligent superstructure over the nitrogen valve control system at the test bench of the superconducting magnets factory in the LHEP. A program has been developed that operates in the Tango Controls environment and performs coordinated control of several valves to stabilize nitrogen pressure in a cryogenic installation. The developed program provides automatic pressure control in a cryogenic installation without disturbing the already existing control level. Further work involves the development of a robotic testing ground for testing and implementing new algorithms and approaches to building robust automatic control systems, including those based on soft computing algorithms and quantum fuzzy neural networks. Information on the seminar and the link to connect are available at Indico. Сonnecting to MTS Link.