Quantum Intelligent Control of Nitrogen Pressure in a Cryogenic Facility of Magnet Plant Test Bench

This paper presents the results of the implementation of information technology for the design of embedded intelligent control systems based on fuzzy logic, neural networks, genetic and quantum algorithms for the problem of nitrogen pressure stabilization in the cryogenic system of the test stand of the JINR VBLHEP magnet factory. A description of the current control system with a built-in quantum controller implementing coordination control is presented. The structure of the developed intelligent control system based on quantum and soft computing technologies is considered on the example of the nitrogen refueling mode. The efficiency of the system has been demonstrated experimentally.