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“Closed and Open Loop Subspace System Identification of the Kalman Filter”

Authors: David Di Ruscio,
Affiliation: Telemark University College
Reference: 2009, Vol 30, No 2, pp. 71-86.

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Keywords: Subspace, Identification, Closed loop, Linear Systems, Modeling

Abstract: Some methods for consistent closed loop subspace system identification presented in the literature are analyzed and compared to a recently published subspace algorithm for both open as well as for closed loop data, the DSR_e algorithm. Some new variants of this algorithm are presented and discussed. Simulation experiments are included in order to illustrate if the algorithms are variance efficient or not.

PDF PDF (350 Kb)        DOI: 10.4173/mic.2009.2.3



DOI forward links to this article:
  [1] David Di Ruscio (2012), doi:10.4173/mic.2012.2.1
  [2] David Di Ruscio (2013), doi:10.4173/mic.2013.3.2
  [3] David Di Ruscio (2009), doi:10.4173/mic.2009.4.2
  [4] Jan-Willem van Wingerden, Marco Lovera, Marco Bergamasco, Michel Verhaegen and Gijs van der Veen (2013), doi:10.1049/iet-cta.2012.0653
  [5] Gijs van der Veen, Jan-Willem van Wingerden and Michel Verhaegen (2013), doi:10.1109/TCST.2012.2205929
  [6] K. Erik J. Olofsson (2013), doi:10.1109/CDC.2013.6761026
  [7] Gijs van der Veen, Jan-Willem van Wingerden and Michel Verhaegen (2010), doi:10.1109/CDC.2010.5717872
  [8] Jinxu Cheng, Mengqi Fang and Youqing Wang (2016), doi:10.1007/s11045-016-0427-y
  [9] Christer Dalen and David Di Ruscio (2016), doi:10.4173/mic.2016.4.2
  [10] Guillaume Mercere, Ivan Markovsky and Jose A. Ramos (2016), doi:10.1109/CDC.2016.7798709


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BibTeX:
@article{MIC-2009-2-3,
  title={{Closed and Open Loop Subspace System Identification of the Kalman Filter}},
  author={Di Ruscio, David},
  journal={Modeling, Identification and Control},
  volume={30},
  number={2},
  pages={71--86},
  year={2009},
  doi={10.4173/mic.2009.2.3},
  publisher={Norwegian Society of Automatic Control}
};

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