Generalized convergence conditions of the parameter adaptation algorithm in discrete-time recursive identification and adaptive control

In this paper, we extend convergence conditions for the parameter adaptation algorithm, used in discrete-time recursive identification schemes, or in adaptive control. Whereas the classical stability analysis of this algorithm consists in checking the strictly real positiveness of an associated tran...

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Veröffentlicht in:Automatica (Oxford) Jg. 92; S. 109 - 114
Hauptverfasser: Vau, Bernard, Bourlès, Henri
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.06.2018
Elsevier
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ISSN:0005-1098, 1873-2836
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Zusammenfassung:In this paper, we extend convergence conditions for the parameter adaptation algorithm, used in discrete-time recursive identification schemes, or in adaptive control. Whereas the classical stability analysis of this algorithm consists in checking the strictly real positiveness of an associated transfer function, we demonstrate that convergence can be obtained even when this condition is not fulfilled, under some assumptions on the algorithm forgetting factors. These results regarding both deterministic and stochastic contexts are obtained by analyzing convergence with a prescribed degree of stability.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2018.02.016