{"title":"第一类Volterra差分方程的最优控制","authors":"M. Alharthi, Tim Hughes, Markus Mueller","doi":"10.1109/Control55989.2022.9781441","DOIUrl":null,"url":null,"abstract":"We consider optimal control for Volterra Difference Equations of the form\\begin{equation*}x(n + 1) = \\sum\\limits_{i = 0}^n B (i)x(n - i) + Cu(n),\\quad n \\in {\\mathbb{Z}^ + }.\\tag{1}\\end{equation*}We show that the optimal control problem can be solved via a Riccati equation or alternatively, and computationally less involved, by solving a linear equation. We consider an application from epidemiology where the optimal control problem admits an optimal solution using the theoretical result. However, the optimal control does not necessarily satisfy constraints of the system?s biology, i.e. non-negativity of the state.","PeriodicalId":101892,"journal":{"name":"2022 UKACC 13th International Conference on Control (CONTROL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Control of Volterra Difference Equations of the First Kind\",\"authors\":\"M. Alharthi, Tim Hughes, Markus Mueller\",\"doi\":\"10.1109/Control55989.2022.9781441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider optimal control for Volterra Difference Equations of the form\\\\begin{equation*}x(n + 1) = \\\\sum\\\\limits_{i = 0}^n B (i)x(n - i) + Cu(n),\\\\quad n \\\\in {\\\\mathbb{Z}^ + }.\\\\tag{1}\\\\end{equation*}We show that the optimal control problem can be solved via a Riccati equation or alternatively, and computationally less involved, by solving a linear equation. We consider an application from epidemiology where the optimal control problem admits an optimal solution using the theoretical result. However, the optimal control does not necessarily satisfy constraints of the system?s biology, i.e. non-negativity of the state.\",\"PeriodicalId\":101892,\"journal\":{\"name\":\"2022 UKACC 13th International Conference on Control (CONTROL)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 UKACC 13th International Conference on Control (CONTROL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Control55989.2022.9781441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 UKACC 13th International Conference on Control (CONTROL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Control55989.2022.9781441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
我们考虑形式为Volterra差分方程的最优控制\begin{equation*}x(n + 1) = \sum\limits_{i = 0}^n B (i)x(n - i) + Cu(n),\quad n \in {\mathbb{Z}^ + }.\tag{1}\end{equation*}我们证明了最优控制问题可以通过Riccati方程来解决,或者通过求解线性方程来解决,并且计算较少。我们考虑了流行病学中的一个应用,其中最优控制问题允许使用理论结果的最优解。然而,最优控制并不一定满足系统的约束条件。S生物学,即非负性的状态。
Optimal Control of Volterra Difference Equations of the First Kind
We consider optimal control for Volterra Difference Equations of the form\begin{equation*}x(n + 1) = \sum\limits_{i = 0}^n B (i)x(n - i) + Cu(n),\quad n \in {\mathbb{Z}^ + }.\tag{1}\end{equation*}We show that the optimal control problem can be solved via a Riccati equation or alternatively, and computationally less involved, by solving a linear equation. We consider an application from epidemiology where the optimal control problem admits an optimal solution using the theoretical result. However, the optimal control does not necessarily satisfy constraints of the system?s biology, i.e. non-negativity of the state.