{"title":"数据驱动控制:二集之一[关于此问题]","authors":"Rodolphe Sepulchre","doi":"10.1109/mcs.2023.3291628","DOIUrl":null,"url":null,"abstract":"This issue of <italic xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">IEEE Control Systems</i> is the first of two special issues devoted to data-driven control. The guest editor for these two issues is Florian Dörfler, and he was helped by our associate editor, Daniel Quevedo. They assembled seven articles for this special issue, the first four of which appear in the present issue: “Data-Driven Control Based on the Behavioral Approach: From Theory to Applications in Power Systems,” by Ivan Markovsky, Linbin Huang, and Florian Dörfler <xref ref-type=\"list-item\" rid=\"list-itemA1\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">[A1]</xref> ; “Kernel Methods and Gaussian Processes for System Identification and Control: A Road Map on Regularized Kernel-Based Learning for Control,” by Algo Carè, Ruggero Carli, Alberto Dalla Libera, Diego Romeres, and Gianluigi Pillonetto <xref ref-type=\"list-item\" rid=\"list-itemA2\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">[A2]</xref> ; “Quasi-Stochastic Approximation: Design Principles With Applications to Extremum Seeking Control,” by Caio Kalil Lauand and Sean Meyn <xref ref-type=\"list-item\" rid=\"list-itemA3\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">[A3]</xref> ; and “Data-Driven Safety Filters: Hamilton-Jacobi Reachability, Control Barrier Functions, and Predictive Methods for Uncertain Systems,” by Kim P. Wabersich, Andrew J. Taylor, Jason J. Choi, Koushil Sreenath, Claire J. Tomlin, Aaron D. Ames, and Melanie N. Zeilinger <xref ref-type=\"list-item\" rid=\"list-itemA4\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">[A4]</xref> . The four articles are described in the introductory article by Guest Editor Florian Dörfler <xref ref-type=\"list-item\" rid=\"list-itemA5\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">[A5]</xref> .","PeriodicalId":55028,"journal":{"name":"IEEE Control Systems Magazine","volume":"25 1","pages":"0"},"PeriodicalIF":3.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data-Driven Control: Part One of Two [About this Issue]\",\"authors\":\"Rodolphe Sepulchre\",\"doi\":\"10.1109/mcs.2023.3291628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This issue of <italic xmlns:mml=\\\"http://www.w3.org/1998/Math/MathML\\\" xmlns:xlink=\\\"http://www.w3.org/1999/xlink\\\">IEEE Control Systems</i> is the first of two special issues devoted to data-driven control. 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引用次数: 0
摘要
本期《IEEE控制系统》是两期关于数据驱动控制的特刊中的第一期。这两期的客座编辑是Florian Dörfler,他得到了我们的副编辑Daniel Quevedo的帮助。他们为本期特刊汇集了七篇文章,其中前四篇出现在本期:“基于行为方法的数据驱动控制:从理论到电力系统的应用”,作者:Ivan Markovsky, Linbin Huang和Florian Dörfler [A1];“系统识别和控制的核方法和高斯过程:基于正则化核的控制学习的路线图”,作者:Algo Carè, Ruggero Carli, Alberto Dalla Libera, Diego Romeres和Gianluigi Pillonetto [A2];Caio Kalil Lauand和Sean Meyn的《准随机逼近:设计原则与极值寻求控制的应用》[A3];和“数据驱动的安全过滤器:Hamilton-Jacobi可达性、控制障碍函数和不确定系统的预测方法”,作者:Kim P. wabersiich、Andrew J. Taylor、Jason J. Choi、Koushil Sreenath、Claire J. Tomlin、Aaron D. Ames和Melanie N. Zeilinger [A4]。客座编辑Florian Dörfler [A5]在介绍文章中介绍了这四篇文章。
Data-Driven Control: Part One of Two [About this Issue]
This issue of IEEE Control Systems is the first of two special issues devoted to data-driven control. The guest editor for these two issues is Florian Dörfler, and he was helped by our associate editor, Daniel Quevedo. They assembled seven articles for this special issue, the first four of which appear in the present issue: “Data-Driven Control Based on the Behavioral Approach: From Theory to Applications in Power Systems,” by Ivan Markovsky, Linbin Huang, and Florian Dörfler [A1] ; “Kernel Methods and Gaussian Processes for System Identification and Control: A Road Map on Regularized Kernel-Based Learning for Control,” by Algo Carè, Ruggero Carli, Alberto Dalla Libera, Diego Romeres, and Gianluigi Pillonetto [A2] ; “Quasi-Stochastic Approximation: Design Principles With Applications to Extremum Seeking Control,” by Caio Kalil Lauand and Sean Meyn [A3] ; and “Data-Driven Safety Filters: Hamilton-Jacobi Reachability, Control Barrier Functions, and Predictive Methods for Uncertain Systems,” by Kim P. Wabersich, Andrew J. Taylor, Jason J. Choi, Koushil Sreenath, Claire J. Tomlin, Aaron D. Ames, and Melanie N. Zeilinger [A4] . The four articles are described in the introductory article by Guest Editor Florian Dörfler [A5] .
期刊介绍:
As the official means of communication for the IEEE Control Systems Society, the IEEE Control Systems Magazine publishes interesting, useful, and informative material on all aspects of control system technology for the benefit of control educators, practitioners, and researchers.