{"title":"负虚系统的时域矩匹配模型约简","authors":"Lanlin Yu, J. Xiong","doi":"10.1109/ICARCV.2018.8581302","DOIUrl":null,"url":null,"abstract":"In this paper, the moment matching model reduction problem for negative imaginary systems is considered in the time-domain framework. For a given high order negative imaginary system with poles at the origin, our goal is to find a reduced-order negative imaginary system such that a prescribed number of the moments and the poles at the origin are preserved. The reduced-order negative imaginary systems was constructed by the parameterized reduced-order systems that match the moments. It shows that a desired reduced-order system can be obtained by using the unique solution of a Sylvester equation. Finally, the proposed model reduction method is illustrated by an RLC network and a train system.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-domain moment matching model reduction for negative imaginary systems\",\"authors\":\"Lanlin Yu, J. Xiong\",\"doi\":\"10.1109/ICARCV.2018.8581302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the moment matching model reduction problem for negative imaginary systems is considered in the time-domain framework. For a given high order negative imaginary system with poles at the origin, our goal is to find a reduced-order negative imaginary system such that a prescribed number of the moments and the poles at the origin are preserved. The reduced-order negative imaginary systems was constructed by the parameterized reduced-order systems that match the moments. It shows that a desired reduced-order system can be obtained by using the unique solution of a Sylvester equation. Finally, the proposed model reduction method is illustrated by an RLC network and a train system.\",\"PeriodicalId\":395380,\"journal\":{\"name\":\"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARCV.2018.8581302\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2018.8581302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time-domain moment matching model reduction for negative imaginary systems
In this paper, the moment matching model reduction problem for negative imaginary systems is considered in the time-domain framework. For a given high order negative imaginary system with poles at the origin, our goal is to find a reduced-order negative imaginary system such that a prescribed number of the moments and the poles at the origin are preserved. The reduced-order negative imaginary systems was constructed by the parameterized reduced-order systems that match the moments. It shows that a desired reduced-order system can be obtained by using the unique solution of a Sylvester equation. Finally, the proposed model reduction method is illustrated by an RLC network and a train system.