{"title":"q参数化中自由传递函数近似的一种新方法","authors":"G. Sanchez, J. Ferrer","doi":"10.1109/CACSD.2004.1393899","DOIUrl":null,"url":null,"abstract":"This paper presents a new approach for approximating the free transfer function in Q-parametrization. Its main advantage is that the number of parameters to be tuned during the design process is reduced, when compared to others methods. As a design example, the \"two-mass and spring\" benchmark control problem was solved, using GESA: an evolutionary non-linear optimization technique","PeriodicalId":111199,"journal":{"name":"2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new approach for approximating the free transfer function in Q-parametrization\",\"authors\":\"G. Sanchez, J. Ferrer\",\"doi\":\"10.1109/CACSD.2004.1393899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new approach for approximating the free transfer function in Q-parametrization. Its main advantage is that the number of parameters to be tuned during the design process is reduced, when compared to others methods. As a design example, the \\\"two-mass and spring\\\" benchmark control problem was solved, using GESA: an evolutionary non-linear optimization technique\",\"PeriodicalId\":111199,\"journal\":{\"name\":\"2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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.2004.1393899\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","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.2004.1393899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new approach for approximating the free transfer function in Q-parametrization
This paper presents a new approach for approximating the free transfer function in Q-parametrization. Its main advantage is that the number of parameters to be tuned during the design process is reduced, when compared to others methods. As a design example, the "two-mass and spring" benchmark control problem was solved, using GESA: an evolutionary non-linear optimization technique