Parameter estimation algorithms for missing-data systems

  • Authors:
  • Feng Ding;Jie Ding

  • Affiliations:
  • School of Communication and Control Engineering, Jiangnan University, Wuxi, P. R. China;School of Communication and Control Engineering, Jiangnan University, Wuxi, P. R. China

  • Venue:
  • ACC'09 Proceedings of the 2009 conference on American Control Conference
  • Year:
  • 2009

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Abstract

This paper considers the problems of parameter identification and output estimation with possibly irregularly missing output data, using output error models. By means of an auxiliary (reference) model approach, we present a recursive least squares algorithm to estimate the parameters of missing data systems, and establish convergence properties for the parameter and missing output estimation in the stochastic framework. The basic idea is to replace the unmeasurable inner variables with the output of an auxiliary model.