文章基本信息

标题：Identification of nonlinear systems and optimality analysis in Sobolev spaces
本地全文：下载
作者：Carlo Novara ; Angelo Nicolí ; Giuseppe C. Calafiore 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：1144-1149
DOI：10.1016/j.ifacol.2020.12.1321
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, we propose a novel approach for the identification from data of an unknown nonlinear function together with its derivatives. This approach can be useful, for instance, in the context of nonlinear system identification for obtaining models that are more reliable than the traditional ones, based on plain function approximation. Indeed, models identified by accounting for the derivatives can provide a better performance in several tasks, such as multi-step prediction, simulation, and control design. We also develop an optimality analysis, showing that models derived using this approach enjoy suitable optimality properties in Sobolev spaces. We finally demonstrate the effectiveness of the approach with a numerical example.
关键词：KeywordsModel identificationnonlinear systemsoptimalityidentification for control