文章基本信息

标题：Enabling Invariant Models to Describe Time-Varying Dynamics: A Case Study ⁎
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作者：Petrus E.O.G.B. Abreu ; Victor D.R. Dreke ; Luis A. Aguirre 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：14
页码：1-6
DOI：10.1016/j.ifacol.2021.10.319
语种：English
出版社：Elsevier
摘要：AbstractThis work addresses the problem of identifying nonlinear and time-varying behaviors using Nonlinear polynomial AutoRegressive models with eXogenous inputs (NARX). Two approaches are investigated. The first one is based on a recursive algorithm with an adaptive forgetting factor to update the parameters of black-box models. The second approach aims to include a certain class of regressors to identify invariant models, i.e. with constant parameters, to describe such behaviors. An experimental case study of a pH neutralization process is carried out, which indicated the presence of behaviors that resemble varying dynamics features. Time-invariant models with a specific class of regressors are proposed and seem to be a promising way to deal with such dynamics.
关键词：KeywordsGray-box identificationpH systemNARX modelvarying dynamics