{"title":"如何利用实验数据改进线性时变系统的鲁棒控制","authors":"M. M. Kogan, A. V. Stepanov","doi":"10.1134/S0005117924060079","DOIUrl":null,"url":null,"abstract":"<p>This paper demonstrates that robust control based on only a priori information about the object’s uncertainty can be significantly improved through the additional use of experimental data. Generalized <i>H</i><sub>∞</sub>-optimal controllers are designed for an unknown linear time-varying system on a finite horizon. These controllers optimize the damping level of exogenous and/or initial disturbances as well as the maximum deviation of the terminal state of the system. The design method does not require the persistent excitation condition or the rank condition, which ensure the identifiability of the system. As a result, the amount of experimental data can be significantly reduced.</p>","PeriodicalId":55411,"journal":{"name":"Automation and Remote Control","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How to Improve Robust Control of a Linear Time-Varying System by Using Experimental Data\",\"authors\":\"M. M. Kogan, A. V. Stepanov\",\"doi\":\"10.1134/S0005117924060079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper demonstrates that robust control based on only a priori information about the object’s uncertainty can be significantly improved through the additional use of experimental data. Generalized <i>H</i><sub>∞</sub>-optimal controllers are designed for an unknown linear time-varying system on a finite horizon. These controllers optimize the damping level of exogenous and/or initial disturbances as well as the maximum deviation of the terminal state of the system. The design method does not require the persistent excitation condition or the rank condition, which ensure the identifiability of the system. As a result, the amount of experimental data can be significantly reduced.</p>\",\"PeriodicalId\":55411,\"journal\":{\"name\":\"Automation and Remote Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automation and Remote Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1134/S0005117924060079\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation and Remote Control","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1134/S0005117924060079","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
How to Improve Robust Control of a Linear Time-Varying System by Using Experimental Data
This paper demonstrates that robust control based on only a priori information about the object’s uncertainty can be significantly improved through the additional use of experimental data. Generalized H∞-optimal controllers are designed for an unknown linear time-varying system on a finite horizon. These controllers optimize the damping level of exogenous and/or initial disturbances as well as the maximum deviation of the terminal state of the system. The design method does not require the persistent excitation condition or the rank condition, which ensure the identifiability of the system. As a result, the amount of experimental data can be significantly reduced.
期刊介绍:
Automation and Remote Control is one of the first journals on control theory. The scope of the journal is control theory problems and applications. The journal publishes reviews, original articles, and short communications (deterministic, stochastic, adaptive, and robust formulations) and its applications (computer control, components and instruments, process control, social and economy control, etc.).