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“Closed Loop Subspace Identification”

Authors: Geir W. Nilsen and David Di Ruscio,
Affiliation: Telemark University College
Reference: 2005, Vol 26, No 3, pp. 151-164.

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Keywords: Closed loop, subspace system identification, Kalman filter, unbiased estimates

Abstract: A new three step closed loop subspace identifications algorithm based on an already existing algorithm and the Kalman filter properties is presented. The Kalman filter contains noise free states which implies that the states and innovation are uneorre lated. The idea is that a Kalman filter found by a good subspace identification algorithm will give an output which is sufficiently uncorrelated with the noise on the output of the actual process. Using feedback from the output of the estimated Kalman filter in the closed loop system a subspace identification algorithm can be used to estimate an unbiased model.

PDF PDF (1518 Kb)        DOI: 10.4173/mic.2005.3.3

DOI forward links to this article:
  [1] Gabriele Pannocchia and Mirco Calosi (2010), doi:10.1016/j.jprocont.2010.01.004

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  title={{Closed Loop Subspace Identification}},
  author={Nilsen, Geir W. and Di Ruscio, David},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}


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