Adaptive and intelligent control of networked and distributed systems (AdIn)
The laboratory was created in October 2021 based on the national project "Science and Universities" and as a result of the competition of the Ministry of Science and Higher Education of the Russian Federation on the creation of youth laboratories on the basis of scientific and educational centers (14.09. 2021 No. BK-P/23).
Head of the laboratory: Doctor of Technical Sciences, Professor Furtat Igor Borisovich
e-mail: cainenash@mail.ru, fib@ipme.ru
Congratulations to Nguyen Ba Hue, a young researcher at the laboratory"Adaptive and Intelligent Control of Network and Distributed Systems" (AdIn), on his successful presentation at the XXIV Young Scientists Conference "Navigation and Traffic Control" (with international participation), which was held from March 15 to 18, 2022 in "Electropribor" (St. Petersburg). Nguyen Ba Hu was awarded a 2nd degree diploma for the best report presented at the section "Measurement Information Processing".
The regulation establishes the types, procedure and conditions for the use of incentive allowances made at the expense of budget financing and ensuring an increase in the effectiveness of the activities of research workers of the lab AdIn.
Speech by I.B.Furtat at the Congress of Young Scientists (December 8-10, 2021, Sochi) with a report on the formation and development of laboratories under the guidance of young researchers:
https://молодыеученые.годнауки.рф/business-programs/
Section in the program: Formation and development of laboratories under the guidance of young researchers.
A new divergent method for studying the stability of dynamical systems, obtained within the framework of the Russian Science Foundation grant No. 18-79-10104 at IPME RAS, has been noted in Russian media such as Kommersant, Nauka TASS, Scientific Russia, News of the Russian Academy of Sciences, Gazeta.RU, Indicator, Poisk.
Sources:
1. Stability/Instability Study and Control of Autonomous Dynamical Systems: Divergence Method; Igor B. furtat; PavelA. Gushchin; IEEE Access Journal, February 2021 DOI: 10.1109/ACCESS.2021.3056942
2. A way has been found to facilitate the prediction of the behavior of a physical model // Kommersant, section science from 03/25/2021
3. Modeling the behavior of a physical model was simplified due to the new theory // Nauka TASS from 03/26/2021
4. A way was found to facilitate the prediction of the behavior of a physical model // Scientific Russia from 03/26/2021
5. A way was found to facilitate the prediction of the behavior of a physical model // News of the Russian Academy of Sciences from 03/26/2021
6. A way was found to facilitate the prediction of the behavior of a physical model // Gazeta.RU from 03/26/2021
7. A way was found to facilitate the prediction of the behavior of a physical model // Indicator from 03/28/2021
8. To be continued. The method of a famous mathematician has been developed // Poisk from 2021.
Laboratory presentation
- RSF, No. 18-79-10104 "Control of network systems under conditions of uncertainty and delay with application to the control of electric power networks" (headed by I.B. Furtat), 2018-2023
- Grant of the President of the Russian Federation, MD-1054.2020.8 "Development of methods and software for optimal control of distributed systems through digital communication channels with application to smart power supply networks" (supervisor I.B. Furtat), 2020-2021
- Megagrant, No. 075-15-2021-573 "Theoretical Foundations of Digitalization of Analysis and Synthesis of Complex Mechanical Systems, Networks and Environments" (mastered by I.B. Furtat), 2021-2023
- RFBR, No. 20-08-00610 "Control methods through noisy data transmission and reception channels with uncontrolled delay" (headed by I.B. Furtat), 2020-2022
- RFBR, 19-08-00246 "Development of methods and algorithms for optimal control of high-dimensional systems under uncertainty with application to the control of the rectification process" (headed by P.A. Gushchin), 2019-2021
The experimental complex is a unique installation for the study and research of power grid control systems. This complex allows you to explore any network management algorithms in normal operation and emergency situations associated with a sudden change in network load.
The principle of operation of the experimental complex
Functional diagram of the experimental complex:
Control systems are three electric generators (model 371.3701), each of which has:
Direct mechanical connection with an electric motor (model 5AIE 71 B2) to set the generator in motion. The excitation winding of the rotor to control the energy generated by the generator. 3 phase output current for unloading. The role of the source of mechanical action on the generators is played by AC electric motors powered by a 220-volt network. The shaft of the motor and the generator is connected by a flexible coupling, on which a disk is fixed for the operation of an optical encoder (model FC-03). The encoder is used to obtain data on the rotation speed of the generator shaft. The received data is transferred directly to the control board (model STM32).
Ballast rheostats (model RB - 302) and inductors from welding machines are used to relieve the load of generators. In this case, the same phases from 3 generators are connected and connected to 3 different load devices. The second terminal of the load device is connected to a common "0" combined with three generators.
Data on the current flowing through the load is provided by 3 AC sensors (model ACS712) connected each to the corresponding load, the signal from the sensors goes to the control board.
The control board consists of two devices connected to each other via UART. The role of the computer on which the control signals are calculated is performed by a personal computer with the MATLAB/Simulink software package installed. The second STM32 board is designed to collect information from sensors, exchange information with a personal computer, and generate a PWM transistor control signal. MOSFET transistors ensure the passage of the required current through the control winding of the generator rotor. They have an external power supply of 12 volts. To adjust the operation of the transistors, current sensors are used in the excitation winding circuit, the signal from which goes to the control board.
List of the main equipment of the experimental complex, containing the name and main characteristics of the devices
- Generator 371.3701. Maximum power 770 W, rated voltage 14 V, maximum current 55 A, rotor speed corresponding to the rated voltage under load - 2000 rpm, 14 V, 35 A.
- Electric motor 5AIE 71 V2 (asynchronous). Power 750 W, rated rotation speed 3000 rpm.
- Speed sensor FC-03 based on LM393 chip. Encoder output interface or type: digital TTL. Field winding current sensor ACS712 20 A. Load current sensor linear AC/DC 57A, CSLA1CD. The maximum measurement current is 57 A. load devices.
- Ballast rheostat "RB-302", which allows you to dissipate up to 315 A at a voltage of 75 V. On this rheostat, the load is switched on in steps, using 6 knife switches, each of which is responsible for its own load circuit. Inductive coils are used to simulate an inductive load, designed for welding machines with a current carrying capacity of up to 300 A.
- Power supplies. To connect the electronics, a minimum constant voltage of 12 V is required (a 200-400 W computer power supply is used). The stand uses a 5V FSPGroupATX-350PNR power supply. A Faraday 100W/24V power supply is used for the excitation winding on each generator.
- Computer on x86 architecture. This device is required to run and use Matlab/Simulink. Debug board based on Atmega and STM microcontrollers. This solution completely covers the required parameters, and also allows you to connect a USB-microUSB cable to a PC and transfer data directly using UART
List of performed typical works
- Testing algorithms for managing a network of electric generators in normal network operation
- Testing algorithms for controlling a network of electric generators with a sudden change in active and reactive loads in the network.
- Debugging of power grid control algorithms.
- Study of the operation of a network of electric generators with constant and variable load in the network.
List of applied measurement techniques
- Measurement, processing of received signals, visualization and control is carried out in real time using computerized tools and involving licensed software MatLab Simulink RealTime 2015.
- The minimum achievable time slicing period is 0.5 sec.
- Measuring the angles of rotation of the rotor - 3 measurements per full revolution.
- Measurement of load currents, nominal interval 40-50 A.There are 6 switches on each of the three phases, stepwise changing the load resistance.
Stand uniqueness degree
- Online monitoring of all parameters in the network.
- Online control of electrical generators.
- Research of any existing control algorithms.
- The study of new algorithms for managing the electric power network.
- Programming control algorithms in the Matlab software environment.
- Designing control algorithms in the form of block diagrams in the Matlab/Simulink software environment.
- Within the framework of megagrant No. 075-15-2021-573, cooperation is being carried out with Tel Aviv University (Israel) and the Ensenada Center for Scientific Research and Higher Education (Mexico).
- Within the framework of the RFBR grant No. 20-08-00610, cooperation is carried out with Gubkin University (Moscow) and Astrakhan State Technical University (Astrakhan).
- Within the framework of the state task, cooperation is carried out with St. Petersburg State University and ITMO University (St. Petersburg).
- Adaptive control robust control
- Nonlinear control
- Optimal control
- Control of dynamic networks and multi-agent systems
- Control of distributed systems (systems of parabolic and hyperbolic type)
- Control in the oil and gas production and processing industry (control of the processes of adsorption, rectification, gas lift operation of oil wells, reservoir pressure maintenance)
- Control of a gearless precision electric drive of an optical telescope axis
- Control of electric power networks in conditions of uncertainties in network parameters, external disturbances and emergencies associated with a sudden change in the reactance of power lines. For practical testing of theoretical results, a unique electric power stand has been developed
Head of the Laboratory
Furtat I.B.
Employees
Furtat I.B.
Nikolay V. Kuznetsov
Vrazhevsky S.A.
