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 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
01.06.2018
Elsevier |
| Schlagworte: | |
| ISSN: | 0005-1098, 1873-2836 |
| Online-Zugang: | Volltext |
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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. |
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| ISSN: | 0005-1098 1873-2836 |
| DOI: | 10.1016/j.automatica.2018.02.016 |