文章基本信息

标题：Data Informativity for the Closed-Loop Identification of MISO ARX Systems
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作者：Kévin Colin ; Laurent Bako ; Xavier Bombois 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：7
页码：779-784
DOI：10.1016/j.ifacol.2021.08.456
语种：English
出版社：Elsevier
摘要：AbstractIn the Prediction Error identification framework, it is crucial that the collected data are informative with respect to the chosen model structure to get a consistent estimate. In this work, we focus on the data informativity property for the identification of multi-inputs single-output ARX systems in closed-loop and we derive a necessary and sufficient condition to verify if a given multisine external excitation combined with the feedback introduced by the controller yields informative data with respect to the chosen model structure.
关键词：KeywordsSystem IdentificationData InformativityPrediction Error MethodConsistency