文章基本信息

标题：Data-driven inference of conic relations via saddle-point dynamics ⁎
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作者：Anne Romer ; Jan Maximilian Montenbruck ; Frank Allgöwer 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：25
页码：396-401
DOI：10.1016/j.ifacol.2018.11.139
语种：English
出版社：Elsevier
摘要：AbstractConic relations of an input-output system are important system properties that can be exploited in order to design robust controllers. Therefore, we study the problem of determining the minimal cone containing such an input-output system. While in applications the input-output relation itself is often undisclosed, input-output data tuples can be sampled. Therefore, we present an iterative sampling approach to determine conic relations of a linear time-invariant system from input-output data. This sampling approach is based on saddle-point dynamics, whose convergence properties are then investigated.
关键词：Keywordslearning algorithmssystem analysisiterative methodsinput-output methods