{"title":"快速计算基于平面控制的扩散问题的函数组成导数","authors":"Stephan Scholz, Lothar Berger","doi":"10.1186/s13362-024-00143-y","DOIUrl":null,"url":null,"abstract":"The chain rule is a standard tool in differential calculus to find derivatives of composite functions. Faà di Bruno’s formula is a generalization of the chain rule and states a method to find high-order derivatives. In this contribution, we propose an algorithm based on Faà di Bruno’s formula and Bell polynomials (Bell in Ann Math 29:38–46, 1927; Parks and Krantz in A primer of real analytic functions, 2012) to compute the structure of derivatives of function compositions. The application of our method is showcased using trajectory planning for the heat equation (Laroche et al. in Int J Robust Nonlinear Control 10(8):629–643, 2000).","PeriodicalId":44012,"journal":{"name":"Journal of Mathematics in Industry","volume":"44 1","pages":""},"PeriodicalIF":1.2000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast computation of function composition derivatives for flatness-based control of diffusion problems\",\"authors\":\"Stephan Scholz, Lothar Berger\",\"doi\":\"10.1186/s13362-024-00143-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The chain rule is a standard tool in differential calculus to find derivatives of composite functions. Faà di Bruno’s formula is a generalization of the chain rule and states a method to find high-order derivatives. In this contribution, we propose an algorithm based on Faà di Bruno’s formula and Bell polynomials (Bell in Ann Math 29:38–46, 1927; Parks and Krantz in A primer of real analytic functions, 2012) to compute the structure of derivatives of function compositions. The application of our method is showcased using trajectory planning for the heat equation (Laroche et al. in Int J Robust Nonlinear Control 10(8):629–643, 2000).\",\"PeriodicalId\":44012,\"journal\":{\"name\":\"Journal of Mathematics in Industry\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mathematics in Industry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s13362-024-00143-y\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematics in Industry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13362-024-00143-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
摘要
链式法则是微分学中求复合函数导数的标准工具。Faà di Bruno 公式是对链式法则的概括,提出了一种求高阶导数的方法。在这篇论文中,我们提出了一种基于 Faà di Bruno 公式和贝尔多项式(Bell,发表于 Ann Math 29:38-46, 1927 年;Parks 和 Krantz,发表于 A primer of real analytic functions, 2012 年)的算法,用于计算函数合成导数的结构。我们的方法在热方程的轨迹规划中得到了应用(Laroche 等人,载于 Int J Robust Nonlinear Control 10(8):629-643, 2000)。
Fast computation of function composition derivatives for flatness-based control of diffusion problems
The chain rule is a standard tool in differential calculus to find derivatives of composite functions. Faà di Bruno’s formula is a generalization of the chain rule and states a method to find high-order derivatives. In this contribution, we propose an algorithm based on Faà di Bruno’s formula and Bell polynomials (Bell in Ann Math 29:38–46, 1927; Parks and Krantz in A primer of real analytic functions, 2012) to compute the structure of derivatives of function compositions. The application of our method is showcased using trajectory planning for the heat equation (Laroche et al. in Int J Robust Nonlinear Control 10(8):629–643, 2000).