{"title":"基于优化的控制器分析","authors":"J. Primbs","doi":"10.1109/ACC.1999.782375","DOIUrl":null,"url":null,"abstract":"Many control techniques employ online optimization in the determination of a control policy. We develop a framework which provides sufficient convex conditions, in the form of linear matrix inequalities, for the analysis of constrained quadratic based optimization schemes. These results encompass standard robustness analysis problems for a wide variety of receding horizon control schemes, including polytopic, structured, and measurement uncertainty for schemes with or without end constraints, observers, or input and output constraints. A simple example illustrates the methodology.","PeriodicalId":441363,"journal":{"name":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":"{\"title\":\"The analysis of optimization based controllers\",\"authors\":\"J. Primbs\",\"doi\":\"10.1109/ACC.1999.782375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many control techniques employ online optimization in the determination of a control policy. We develop a framework which provides sufficient convex conditions, in the form of linear matrix inequalities, for the analysis of constrained quadratic based optimization schemes. These results encompass standard robustness analysis problems for a wide variety of receding horizon control schemes, including polytopic, structured, and measurement uncertainty for schemes with or without end constraints, observers, or input and output constraints. A simple example illustrates the methodology.\",\"PeriodicalId\":441363,\"journal\":{\"name\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"48\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.1999.782375\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.1999.782375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Many control techniques employ online optimization in the determination of a control policy. We develop a framework which provides sufficient convex conditions, in the form of linear matrix inequalities, for the analysis of constrained quadratic based optimization schemes. These results encompass standard robustness analysis problems for a wide variety of receding horizon control schemes, including polytopic, structured, and measurement uncertainty for schemes with or without end constraints, observers, or input and output constraints. A simple example illustrates the methodology.