A fast algorithm to assess local structural identifiability

Research output: Contribution to journalArticleAcademicpeer-review

21 Citations (Scopus)

Abstract

The paper presents a novel method for assessing the local structural identifiability question for a general non-linear state-space model. The method is a combination of (i) the application of a singular value decomposition to a parametric output sensitivity matrix that is created by simply integrating the model once and, (ii) a symbolic computation for a reduced model that is guided by the SVD results and allows a confirmation of the conclusions regarding identifiability obtained in the first step. In case there is a lack of identifiability, the symbolic computation quickly results in determination of the exact structure of the nullspace and a suitable re-parametrisation. The method is discussed in detail and applied to three case studies, of which the last two are considerably large, containing 22 and 43 parameters to be identified, respectively.

Original languageEnglish
Pages (from-to)118-124
JournalAutomatica
Volume58
DOIs
Publication statusPublished - 2015

Keywords

  • Identifiability
  • Parameter identification

Fingerprint Dive into the research topics of 'A fast algorithm to assess local structural identifiability'. Together they form a unique fingerprint.

Cite this