{"title":"离散系统的最小燃料控制问题","authors":"Chaw-Bing Chang","doi":"10.1109/CDC.1975.270606","DOIUrl":null,"url":null,"abstract":"It is known that the minimum fuel control problem is equivalent to a minimum l1 norm problem with linear equality constraints. By applying the dual space theory of linear vector spaces, the minimum l1 norm can be found by maximizing a linear functional with a l¿ norm constraint. This maximization enables the application of a linear programming technique which is usually very efficient. The control sequence which achieves the minimum fuel cost is then found by applying the alignment property in the dual space.","PeriodicalId":164707,"journal":{"name":"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1975-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the minimum fuel control problem for discrete systems\",\"authors\":\"Chaw-Bing Chang\",\"doi\":\"10.1109/CDC.1975.270606\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is known that the minimum fuel control problem is equivalent to a minimum l1 norm problem with linear equality constraints. By applying the dual space theory of linear vector spaces, the minimum l1 norm can be found by maximizing a linear functional with a l¿ norm constraint. This maximization enables the application of a linear programming technique which is usually very efficient. The control sequence which achieves the minimum fuel cost is then found by applying the alignment property in the dual space.\",\"PeriodicalId\":164707,\"journal\":{\"name\":\"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1975-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1975.270606\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1975 IEEE Conference on Decision and Control including the 14th Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1975.270606","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the minimum fuel control problem for discrete systems
It is known that the minimum fuel control problem is equivalent to a minimum l1 norm problem with linear equality constraints. By applying the dual space theory of linear vector spaces, the minimum l1 norm can be found by maximizing a linear functional with a l¿ norm constraint. This maximization enables the application of a linear programming technique which is usually very efficient. The control sequence which achieves the minimum fuel cost is then found by applying the alignment property in the dual space.