Hierarchical Gradient-Based Iterative Parameter Estimation Algorithms for a Nonlinear Feedback System Based on the Hierarchical Identification Principle
This paper focuses on iterative parameter estimation methods for a nonlinear closed-loop system (i.e., a nonlinear feedback system) with an equation-error model for the open-loop part. By applying negative gradient search, a gradient-based iterative algorithm is constructed. To reduce the computatio...
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Veröffentlicht in: | Circuits, systems, and signal processing systems, and signal processing, 2024, Vol.43 (1), p.124-151 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper focuses on iterative parameter estimation methods for a nonlinear closed-loop system (i.e., a nonlinear feedback system) with an equation-error model for the open-loop part. By applying negative gradient search, a gradient-based iterative algorithm is constructed. To reduce the computational costs and improve the parameter estimation accuracy, the hierarchical identification principle is employed to derive a hierarchical gradient-based iterative algorithm. A simulation example is provided to test the effectiveness of the proposed algorithms. |
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ISSN: | 0278-081X 1531-5878 |
DOI: | 10.1007/s00034-023-02477-1 |