A recursive estimation approach to distributed identification of large-scale multi-input-single-output FIR systems

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Abstract

The problem of identifying single modules in multiple-input-single-output (MISO) systems is considered. A novel approach to distributed identification of MISO finite impulse response systems is presented. The distributed identification is discerned by the local estimation of local parameters, which correspond to a module in the MISO system. The local estimators are derived from the standard recursive least squares estimator and require limited information exchange. By Lyapunov's second method, sufficient conditions are derived for asymptotic convergence of the estimators to the true parameters in the absence of disturbances, which lead to asymptotic unbiasedness in the presence of additive output disturbances.

Original languageEnglish
Pages (from-to)236-241
Number of pages6
JournalIFAC-PapersOnLine
Volume51
Issue number23
DOIs
Publication statusPublished - 2018
Event7th IFAC Workshop on Distributed Estimation and Control in Networked Systems NECSYS 2018 - Groningen, Netherlands
Duration: 27 Aug 201828 Aug 2018

Keywords

  • convergence
  • distributed estimation
  • identification
  • Lyapunov methods
  • recursive methods

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