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  • 标题:Set-membership identifiability of nonlinear models and related parameter estimation properties
  • 本地全文:下载
  • 作者:Carine Jauberthie ; Louise Travé-Massuyès ; Nathalie Verdière
  • 期刊名称:International Journal of Applied Mathematics and Computer Science
  • 电子版ISSN:2083-8492
  • 出版年度:2016
  • 卷号:26
  • 期号:4
  • DOI:10.1515/amcs-2016-0057
  • 出版社:De Gruyter Open
  • 摘要:Identifiability guarantees that the mathematical model of a dynamic system is well defined in the sense that it maps unambiguously its parameters to the output trajectories. This paper casts identifiability in a set-membership (SM) framework and relates recently introduced properties, namely, SM-identifiability, μ -SM-identifiability, and ε -SM-identifiability, to the properties of parameter estimation problems. Soundness and ε -consistency are proposed to characterize these problems and the solution returned by the algorithm used to solve them. This paper also contributes by carefully motivating and comparing SM-identifiability, μ -SM-identifiability and ε -SM-identifiability with related properties found in the literature, and by providing a method based on differential algebra to check these properties.
  • 关键词:identifiability; bounded uncertainty; set-membership estimation; nonlinear dynamic models
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