{"title":"能源设施PID控制器自整定块","authors":"I. Shcherbatov, A. Dolgushev","doi":"10.1109/REEPE49198.2020.9059221","DOIUrl":null,"url":null,"abstract":"A neural network block for auto-tuning the PID controller for energy facilities has been implemented. Special attention is paid to the analysis of the comparison of a single-circuit system with a PID controller and a single-circuit system with a neural network auto-tuning unit and a PID controller. The results obtained allow us to conclude that in the process of changing the parameters of an object, a significant superiority is illustrated by the use of a neural network auto-tuning unit.","PeriodicalId":142369,"journal":{"name":"2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Auto tuning block of the PID controller of energy facilities\",\"authors\":\"I. Shcherbatov, A. Dolgushev\",\"doi\":\"10.1109/REEPE49198.2020.9059221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A neural network block for auto-tuning the PID controller for energy facilities has been implemented. Special attention is paid to the analysis of the comparison of a single-circuit system with a PID controller and a single-circuit system with a neural network auto-tuning unit and a PID controller. The results obtained allow us to conclude that in the process of changing the parameters of an object, a significant superiority is illustrated by the use of a neural network auto-tuning unit.\",\"PeriodicalId\":142369,\"journal\":{\"name\":\"2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/REEPE49198.2020.9059221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REEPE49198.2020.9059221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Auto tuning block of the PID controller of energy facilities
A neural network block for auto-tuning the PID controller for energy facilities has been implemented. Special attention is paid to the analysis of the comparison of a single-circuit system with a PID controller and a single-circuit system with a neural network auto-tuning unit and a PID controller. The results obtained allow us to conclude that in the process of changing the parameters of an object, a significant superiority is illustrated by the use of a neural network auto-tuning unit.