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ArticleOriginal scientific text

Title

Set-membership identifiability of nonlinear models and related parameter estimation properties

Authors 1, 1, 2

Affiliations

  1. LAAS-CNRS, University of Toulouse, UPS, 7 avenue du Colonel Roche, 31400 Toulouse, France
  2. UNIHAVRE, LMAH, Normandy University, FR-CNRS-3335, ISCN, 76600 Le Havre, France

Abstract

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.

Keywords

ENG
POL
identifiability, bounded uncertainty, set membership estimation, nonlinear dynamic model

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Additional information

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.

International Journal of Applied Mathematics and Computer Science
2016/26/4
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Pages:
803-813
Main language of publication
English
Published
2016

DOI: 10.1515/amcs-2016-0057

Exact and natural sciences