Open AccessResearch of the influence of feedback signals in the neuroregulator on the quality of regulation
Author(s) -
D. A. Dementev,
Ekaterina D. Maximova,
Ivan A. Sysoletin,
S. V. Mezin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1889/2/022053
Subject(s) - automation , quality (philosophy) , object (grammar) , modular design , relation (database) , regulator , table (database) , computer science , artificial neural network , control (management) , artificial intelligence , control engineering , control theory (sociology) , data mining , engineering , mechanical engineering , philosophy , biochemistry , chemistry , epistemology , gene , operating system
This paper describes the research of the influence of feedback signals in the neuroregulator on the quality of regulation. The approach to creation of a method of development of automatic control systems using artificial neural networks as a regulator with consideration of real technical equipment of automation is described. The effectiveness of feedback in a neural regulator is analysed by carrying out a complex study in relation to the variation of the object’s parameters. For a clear comparison, the transients for each object configuration have been summarised in common graphs. In addition, in order to analyse the effectiveness of the selected configuration, a modular quality index was calculated for each case and these values are tabulated in a common table.