{"title":"奇异摄动系统最优控制方法综述","authors":"Hao Nie, Jinna Li","doi":"10.1109/DDCLS58216.2023.10166648","DOIUrl":null,"url":null,"abstract":"Optimal control design methods for multiple time-scale systems are a hot research topic in recent years. In this paper, a comprehensive overview of the design methods for optimal control of multiple time-scale systems is presented. Firstly, the mathematical model of the optimal control problem of multiple time-scale systems is given, and the key difficulties of the related research are analysed. Secondly, the design methods for optimal control of multiple time-scale systems based on the model and reinforcement learning (RL) methods are given respectively. Thirdly, the performance analysis and practical application of the multi-time scale system are analyzed. Finally, the current problems in solving the optimization of multiple time-scale systems are analysed, and the research directions of optimal control of multiple time-scale systems are prospected.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Overview of Optimal Control Methods for Singularly Perturbed Systems\",\"authors\":\"Hao Nie, Jinna Li\",\"doi\":\"10.1109/DDCLS58216.2023.10166648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimal control design methods for multiple time-scale systems are a hot research topic in recent years. In this paper, a comprehensive overview of the design methods for optimal control of multiple time-scale systems is presented. Firstly, the mathematical model of the optimal control problem of multiple time-scale systems is given, and the key difficulties of the related research are analysed. Secondly, the design methods for optimal control of multiple time-scale systems based on the model and reinforcement learning (RL) methods are given respectively. Thirdly, the performance analysis and practical application of the multi-time scale system are analyzed. Finally, the current problems in solving the optimization of multiple time-scale systems are analysed, and the research directions of optimal control of multiple time-scale systems are prospected.\",\"PeriodicalId\":415532,\"journal\":{\"name\":\"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS58216.2023.10166648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS58216.2023.10166648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Overview of Optimal Control Methods for Singularly Perturbed Systems
Optimal control design methods for multiple time-scale systems are a hot research topic in recent years. In this paper, a comprehensive overview of the design methods for optimal control of multiple time-scale systems is presented. Firstly, the mathematical model of the optimal control problem of multiple time-scale systems is given, and the key difficulties of the related research are analysed. Secondly, the design methods for optimal control of multiple time-scale systems based on the model and reinforcement learning (RL) methods are given respectively. Thirdly, the performance analysis and practical application of the multi-time scale system are analyzed. Finally, the current problems in solving the optimization of multiple time-scale systems are analysed, and the research directions of optimal control of multiple time-scale systems are prospected.