{"title":"当使用远未来前馈信息时,参数方法用于预测控制的可行性","authors":"Shukri Dughman, J. Rossiter","doi":"10.1109/ICCA.2017.8003215","DOIUrl":null,"url":null,"abstract":"This paper considers the tractability of parametric solvers for predictive control based optimisations, when future target information is incorporated. it is shown that the inclusion of future target information can significantly increase the implied parametric dimension to an extent that is undesirable and likely to lead to intractable problems. The paper then proposes some alternative methods for incorporating the desired target information, while minimising he implied growth in the parametric dimensions, at some possibly small cost to optimality.","PeriodicalId":379025,"journal":{"name":"2017 13th IEEE International Conference on Control & Automation (ICCA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The feasibility of parametric approaches to predictive control when using far future feed forward information\",\"authors\":\"Shukri Dughman, J. Rossiter\",\"doi\":\"10.1109/ICCA.2017.8003215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the tractability of parametric solvers for predictive control based optimisations, when future target information is incorporated. it is shown that the inclusion of future target information can significantly increase the implied parametric dimension to an extent that is undesirable and likely to lead to intractable problems. The paper then proposes some alternative methods for incorporating the desired target information, while minimising he implied growth in the parametric dimensions, at some possibly small cost to optimality.\",\"PeriodicalId\":379025,\"journal\":{\"name\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2017.8003215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE International Conference on Control & Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2017.8003215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The feasibility of parametric approaches to predictive control when using far future feed forward information
This paper considers the tractability of parametric solvers for predictive control based optimisations, when future target information is incorporated. it is shown that the inclusion of future target information can significantly increase the implied parametric dimension to an extent that is undesirable and likely to lead to intractable problems. The paper then proposes some alternative methods for incorporating the desired target information, while minimising he implied growth in the parametric dimensions, at some possibly small cost to optimality.