{"title":"瞬态能量增长反馈控制的降阶模型","authors":"Aniketh Kalur, Maziar S. Hemati","doi":"10.2514/6.2018-3690","DOIUrl":null,"url":null,"abstract":"Feedback flow control is developed to suppress the transient energy growth of flow disturbances in a linearized channel flow. Specifically, we seek a controller that minimizes the maximum transient energy growth, which can be formulated as a linear matrix inequality problem. Solving linear matrix inequality problems can be computationally prohibitive for high-dimensional systems encountered in flow control applications. Thus, we develop reduced-order fluids models using balance truncation and proper orthogonal decomposition techniques. These models are designed to optimally approximate system energy while preserving the input-output dynamics that are essential for controller synthesis. Controllers developed based on these reduced-order models are found to reduce transient energy growth and to outperform linear quadratic controllers in the context of a linearized channel flow.","PeriodicalId":144668,"journal":{"name":"2018 Flow Control Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Reduced-Order Models for Feedback Control of Transient Energy Growth\",\"authors\":\"Aniketh Kalur, Maziar S. Hemati\",\"doi\":\"10.2514/6.2018-3690\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Feedback flow control is developed to suppress the transient energy growth of flow disturbances in a linearized channel flow. Specifically, we seek a controller that minimizes the maximum transient energy growth, which can be formulated as a linear matrix inequality problem. Solving linear matrix inequality problems can be computationally prohibitive for high-dimensional systems encountered in flow control applications. Thus, we develop reduced-order fluids models using balance truncation and proper orthogonal decomposition techniques. These models are designed to optimally approximate system energy while preserving the input-output dynamics that are essential for controller synthesis. Controllers developed based on these reduced-order models are found to reduce transient energy growth and to outperform linear quadratic controllers in the context of a linearized channel flow.\",\"PeriodicalId\":144668,\"journal\":{\"name\":\"2018 Flow Control Conference\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Flow Control Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2514/6.2018-3690\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Flow Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/6.2018-3690","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reduced-Order Models for Feedback Control of Transient Energy Growth
Feedback flow control is developed to suppress the transient energy growth of flow disturbances in a linearized channel flow. Specifically, we seek a controller that minimizes the maximum transient energy growth, which can be formulated as a linear matrix inequality problem. Solving linear matrix inequality problems can be computationally prohibitive for high-dimensional systems encountered in flow control applications. Thus, we develop reduced-order fluids models using balance truncation and proper orthogonal decomposition techniques. These models are designed to optimally approximate system energy while preserving the input-output dynamics that are essential for controller synthesis. Controllers developed based on these reduced-order models are found to reduce transient energy growth and to outperform linear quadratic controllers in the context of a linearized channel flow.