Optimal input design for minimum-variance estimation of parameters in nonlinear state-space models

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Abstract

The paper presents a methodology for optimal input design (OID) for minimum-variance estimation of parameters in nonlinear state-space models. To allow analytical solutions, in Keesman (2015) asequential OID approach, based on Pontryagin's minimum principle, was proposed for low-dimensional non-linear systems that are affine in their input. In this study, a simultaneous OID approach for a set of two parameters in one-dimensional non-linear systems affine in their input is presented. For the two-parameter case still analytically tractable solutions are found, unlike cases with three or more parameters.

Original languageEnglish
Pages (from-to)365-370
JournalIFAC-PapersOnLine
Volume51
Issue number15
DOIs
Publication statusPublished - 8 Oct 2018

Keywords

  • Non-linear dynamic systems
  • Optimal Input Design
  • Parameter estimation
  • Pontryagin's principle
  • Two-parameter case

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