{"title":"Enhanced LFR-toolbox for MATLAB","authors":"S. Hecker, A. Varga, J. Magni","doi":"10.1109/CACSD.2004.1393845","DOIUrl":null,"url":null,"abstract":"We describe recent developments and enhancements of the LFR-toolbox for MATLAB for building LFT-based uncertainty models. A major development is the new LFT-object definition supporting a large class of uncertainty descriptions: continuous- and discrete-time uncertain models, regular and singular parametric expressions, more general uncertainty blocks (nonlinear, time-varying, etc.). By associating names to uncertainty blocks the reusability of generated LFT-models and the user friendliness of manipulation of LFR-descriptions have been highly increased. Significant enhancements of the computational efficiency and of numerical accuracy have been achieved by employing efficient and numerically robust FORTRAN implementations of order reduction tools via Mex-function interfaces. The new enhancements in conjunction with improved symbolical preprocessing lead generally to a faster generation of LFT-models with significantly lower orders","PeriodicalId":111199,"journal":{"name":"2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"86","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACSD.2004.1393845","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 86
Abstract
We describe recent developments and enhancements of the LFR-toolbox for MATLAB for building LFT-based uncertainty models. A major development is the new LFT-object definition supporting a large class of uncertainty descriptions: continuous- and discrete-time uncertain models, regular and singular parametric expressions, more general uncertainty blocks (nonlinear, time-varying, etc.). By associating names to uncertainty blocks the reusability of generated LFT-models and the user friendliness of manipulation of LFR-descriptions have been highly increased. Significant enhancements of the computational efficiency and of numerical accuracy have been achieved by employing efficient and numerically robust FORTRAN implementations of order reduction tools via Mex-function interfaces. The new enhancements in conjunction with improved symbolical preprocessing lead generally to a faster generation of LFT-models with significantly lower orders