{"title":"积分-微分最优控制问题变分离散混合有限元方法的后验误差估计","authors":"Zuliang Lu, Dayong Liu","doi":"10.1109/ICEEE.2013.6676039","DOIUrl":null,"url":null,"abstract":"In this paper we study a posteriori error estimates of all discretization parameters for quadratic convex optimal control problems governed by integro-differential equations by using the variational discretization mixed finite element methods. The state and co-state are approximated by the lowest order Raviart-Thomas mixed finite element spaces and the control is not approximated. By applying some error estimates results of mixed finite element methods for integro-differential equations, we derive a posteriori error estimates both for the coupled state and the control approximation of the optimal control problem.","PeriodicalId":226547,"journal":{"name":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A posteriori error estimates of variational discretization mixed finite element methods for integro-differential optimal control problem\",\"authors\":\"Zuliang Lu, Dayong Liu\",\"doi\":\"10.1109/ICEEE.2013.6676039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we study a posteriori error estimates of all discretization parameters for quadratic convex optimal control problems governed by integro-differential equations by using the variational discretization mixed finite element methods. The state and co-state are approximated by the lowest order Raviart-Thomas mixed finite element spaces and the control is not approximated. By applying some error estimates results of mixed finite element methods for integro-differential equations, we derive a posteriori error estimates both for the coupled state and the control approximation of the optimal control problem.\",\"PeriodicalId\":226547,\"journal\":{\"name\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEE.2013.6676039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE.2013.6676039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A posteriori error estimates of variational discretization mixed finite element methods for integro-differential optimal control problem
In this paper we study a posteriori error estimates of all discretization parameters for quadratic convex optimal control problems governed by integro-differential equations by using the variational discretization mixed finite element methods. The state and co-state are approximated by the lowest order Raviart-Thomas mixed finite element spaces and the control is not approximated. By applying some error estimates results of mixed finite element methods for integro-differential equations, we derive a posteriori error estimates both for the coupled state and the control approximation of the optimal control problem.