An efficient hierarchical identification method for general dual-rate sampled-data systems

For the lifted input–output representation of general dual-rate sampled-data systems, this paper presents a decomposition based recursive least squares (D-LS) identification algorithm using the hierarchical identification principle. Compared with the recursive least squares (RLS) algorithm, the prop...

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Veröffentlicht in:Automatica (Oxford) Jg. 50; H. 3; S. 962 - 970
Hauptverfasser: Liu, Yanjun, Ding, Feng, Shi, Yang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier Ltd 01.03.2014
Elsevier
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ISSN:0005-1098, 1873-2836
Online-Zugang:Volltext
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Zusammenfassung:For the lifted input–output representation of general dual-rate sampled-data systems, this paper presents a decomposition based recursive least squares (D-LS) identification algorithm using the hierarchical identification principle. Compared with the recursive least squares (RLS) algorithm, the proposed D-LS algorithm does not require computing the covariance matrices with large sizes and matrix inverses in each recursion step, and thus has a higher computational efficiency than the RLS algorithm. The performance analysis of the D-LS algorithm indicates that the parameter estimates can converge to their true values. A simulation example is given to confirm the convergence results.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2013.12.025