{"title":"函数仿射LPV状态空间表示与LFT模型的等价性","authors":"Mihály Petreczky;Ziad Alkhoury;Guillaume Mercère","doi":"10.1109/LCSYS.2025.3584839","DOIUrl":null,"url":null,"abstract":"We propose a transformation algorithm for a class of Linear Parameter-Varying (LPV) systems with functional affine dependence on parameters, where the system matrices depend affinely on nonlinear functions of the scheduling variable, into Linear Fractional Transformation (LFT) systems. The transformation preserves input-output behavior and minimality, and the uncertainity block of the resulting LFT system is linear in the scheduling variables.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"9 ","pages":"1874-1879"},"PeriodicalIF":2.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Equivalence Between Functionally Affine LPV State-Space Representations and LFT Models\",\"authors\":\"Mihály Petreczky;Ziad Alkhoury;Guillaume Mercère\",\"doi\":\"10.1109/LCSYS.2025.3584839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a transformation algorithm for a class of Linear Parameter-Varying (LPV) systems with functional affine dependence on parameters, where the system matrices depend affinely on nonlinear functions of the scheduling variable, into Linear Fractional Transformation (LFT) systems. The transformation preserves input-output behavior and minimality, and the uncertainity block of the resulting LFT system is linear in the scheduling variables.\",\"PeriodicalId\":37235,\"journal\":{\"name\":\"IEEE Control Systems Letters\",\"volume\":\"9 \",\"pages\":\"1874-1879\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Control Systems Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11062621/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Control Systems Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11062621/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
On the Equivalence Between Functionally Affine LPV State-Space Representations and LFT Models
We propose a transformation algorithm for a class of Linear Parameter-Varying (LPV) systems with functional affine dependence on parameters, where the system matrices depend affinely on nonlinear functions of the scheduling variable, into Linear Fractional Transformation (LFT) systems. The transformation preserves input-output behavior and minimality, and the uncertainity block of the resulting LFT system is linear in the scheduling variables.