Analysis of the Application of Machine Learning in Automatic Control Systems

被引:0
|
作者
Sviridov, Alexey [1 ]
Bobkov, Vladislav [1 ]
Lemza, Anastasia [1 ]
Balashov, Alexander [1 ]
Bobrikov, Dmitriy [1 ]
机构
[1] Natl Res Univ Elect Technol MIET, Moscow, Russia
关键词
automation; control systems; machine learning; optimization; product defect detection; monitoring;
D O I
10.1109/ElConRus51938.2021.9396094
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the modern world, automation affects almost all possible areas of human work. Currently, machine learning and neural networks attract a lot of attention in the technical field. In this regard, systems for automatic monitoring and analysis of automated systems are widely used. Machine learning and neural networks can significantly improve the efficiency of monitoring equipment, detecting product defects, and managing various parameters. The article discusses and analyzes the use of machine learning in such automatic control and monitoring systems. Various automatic control systems, monitoring the condition of equipment, testing the electrical parameters of electronic components, and detecting product defects are considered. Possible positive and negative aspects of applying machine learning to them are analyzed.
引用
收藏
页数:4
相关论文
共 50 条
  • [31] A machine learning approach for automatic operational modal analysis
    Mugnaini, Vezio
    Fragonara, Luca Zanotti
    Civera, Marco
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2022, 170
  • [32] Machine learning and automatic linguistic analysis: The next step
    Brill, E
    [J]. PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6, 1998, : 1033 - 1036
  • [33] A machine learning based control of chaotic systems
    Garcia, P.
    [J]. CHAOS SOLITONS & FRACTALS, 2022, 155
  • [34] MICROPROCESSOR CONTROL OF THE AUTOMATIC SYSTEMS OF NC MACHINE-TOOLS
    SOSONKIN, VL
    [J]. SOVIET ENGINEERING RESEARCH, 1982, 2 (11): : 67 - 71
  • [35] Machine methods of image analysis in automatic inspection systems
    Shelest, DK
    [J]. RUSSIAN JOURNAL OF NONDESTRUCTIVE TESTING, 1995, 31 (05) : 335 - 343
  • [36] WASTEWATER CONTROL WITH THE HELP OF AN AUTOMATIC-ANALYSIS MACHINE
    WILHOLM, G
    [J]. GALVANOTECHNIK, 1981, 72 (02): : 165 - 166
  • [37] LEARNING TO CONTROL DYNAMIC-SYSTEMS WITH AUTOMATIC QUANTIZATION
    LING, CX
    BUCHAL, R
    [J]. ADAPTIVE BEHAVIOR, 1994, 3 (01) : 29 - 49
  • [38] Unified Automatic Control of Vehicular Systems With Reinforcement Learning
    Yan, Zhongxia
    Kreidieh, Abdul Rahman
    Vinitsky, Eugene
    Bayen, Alexandre M.
    Wu, Cathy
    [J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 20 (02) : 789 - 804
  • [39] Ease.ml/snoopy in Action: Towards Automatic Feasibility Analysis for Machine Learning Application Development
    Renggli, Cedric
    Rimanic, Luka
    Kolar, Luka
    Wu, Wentao
    Zhang, Ce
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2020, 13 (12): : 2837 - 2840
  • [40] Application of K-Means Clustering Algorithm in Automatic Machine Learning
    [J]. Ji, Dongri (jidongri0016@163.com), 1600, Springer Science and Business Media Deutschland GmbH (1131):