{"title":"线性系统模型约简中平衡POD算法的变化","authors":"J. Singler","doi":"10.1109/ACC.2013.6579886","DOIUrl":null,"url":null,"abstract":"We present a variation on an existing model reduction algorithm for linear systems based on balanced proper orthogonal decomposition (POD). In contrast to many computational approaches to balanced truncation, the algorithm variation approximates the reduced order model directly without first transforming the linear system. The algorithm is applicable to large-scale finite dimensional systems and a class of infinite dimensional systems. The algorithm variation is compared to the original balanced POD algorithm on example partial differential equation systems.","PeriodicalId":145065,"journal":{"name":"2013 American Control Conference","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Variation of the balanced POD algorithm for model reduction of linear systems\",\"authors\":\"J. Singler\",\"doi\":\"10.1109/ACC.2013.6579886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a variation on an existing model reduction algorithm for linear systems based on balanced proper orthogonal decomposition (POD). In contrast to many computational approaches to balanced truncation, the algorithm variation approximates the reduced order model directly without first transforming the linear system. The algorithm is applicable to large-scale finite dimensional systems and a class of infinite dimensional systems. The algorithm variation is compared to the original balanced POD algorithm on example partial differential equation systems.\",\"PeriodicalId\":145065,\"journal\":{\"name\":\"2013 American Control Conference\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 American Control Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACC.2013.6579886\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 American Control Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACC.2013.6579886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Variation of the balanced POD algorithm for model reduction of linear systems
We present a variation on an existing model reduction algorithm for linear systems based on balanced proper orthogonal decomposition (POD). In contrast to many computational approaches to balanced truncation, the algorithm variation approximates the reduced order model directly without first transforming the linear system. The algorithm is applicable to large-scale finite dimensional systems and a class of infinite dimensional systems. The algorithm variation is compared to the original balanced POD algorithm on example partial differential equation systems.