employee
Institute of Design-Technological Informatics of RAS (Senior scientific assistant)
employee
Moskva, Moscow, Russian Federation
Models of equipment and technological processes based on neural networks with a commutator structure are developed. The article proposes to use neural network models in automated control systems (ACS). Neural network models make it possible to implement automated control systems with a flexible programmable switching structure, quickly connect and disconnect new technological equipment, change the operation order in technological processes, and adapt the system to changing conditions and the external environment. The object of study is ACS. The method is modelling. The aim is to reduce the cost of developing and using automated control systems.
automated control system, flexible programmable structure, artificial neural network, switching structure, neural network model
1. Solomentsev Yu.M., Sosonkin V.L. Flexible Manufacturing System Control. Moscow: Mashinostroenie, 1988. 352 p.
2. Sukhanova N.V. Development of Requirements to Hardware-Software Complex of Intelligent Systems of Control in Mechanical Engineering. Science Intensive Technologies in Mechanical Engineering, 2018, no. 12 (90), pp. 38-43.
3. Sukhanova N.V. Development of Intelligent Auto-mated Control Systems in Mechanical Engineering. Science Intensive Technologies in Mechanical Engineering, 2018, no. 11 (89), pp. 42-46.
4. Sukhanova N.V. Ensuring Fault Tolerance of Auto-mated Control Systems. Quality. Innovation. Education, 2018, no. 2 (153), pp. 23-29.
5. Sukhanova N.V. Developing and Researching a Method for Monitoring the Automated Control System Performance Based on Artificial Neural Networks. Bulletin of Bryansk State Technical University, 2018, no. 7, pp. 91-98.
6. Sukhanova N.V. Ensuring Fault Tolerance of Auto-mated Control System Hardware. Bulletin of MSTU “STANKIN”, 2017, no. 2 (41), pp. 79-83.
7. Sukhanova N.V. Using a Commutator Structure in Ensuring Fault Tolerance of Computer System Hard-ware. Bulletin of MSTU “STANKIN”, 2017, no. 3 (42), pp. 105-110.
8. Kabak I.S., Sukhanova N.V. Patent for Utility Model 75247 Russian Federation MPK 7 G06F15/16 Modular computer system. No. 2008106859; applied on 26th of February 2008; published on the 27th of July, 2008, Bull. No. 21. 2 p.
9. Solomentsev Yu.M., Sheptunov S.A., Kabak I.S., Sukhanova N.V. Patent for invention 2398281 Russian Federation MPK 7 G06N 3/06 Multilayer Modular Computer: Applicant and Patent Holder Federal State Public Scientific Establishment Institute of Information Technology in Design and Engineering of the Russian Academy of Sciences (IKTI RAS). No. 2008143737; applied on the 7th of November 2008; published on the 27th of August 2010, Bull. No. 24. 8 p.
10. Galushkin, A.I. Synthesis of Multilayer Image Recognition Systems. Moscow: Energiya, 1974. 367 p.
11. Ross Ashby W. An Introduction to Cybernetics. Foreign Languages Publishing House, 1959. pp. 127-169.
