Version 1
: Received: 8 January 2023 / Approved: 9 January 2023 / Online: 9 January 2023 (07:46:28 CET)
Version 2
: Received: 9 January 2023 / Approved: 10 January 2023 / Online: 10 January 2023 (03:12:16 CET)
How to cite:
Karabutov, N. Adaptive Parametric Identification of Systems with Multiple Nonlinearities. Preprints2023, 2023010151. https://doi.org/10.20944/preprints202301.0151.v2
Karabutov, N. Adaptive Parametric Identification of Systems with Multiple Nonlinearities. Preprints 2023, 2023010151. https://doi.org/10.20944/preprints202301.0151.v2
Karabutov, N. Adaptive Parametric Identification of Systems with Multiple Nonlinearities. Preprints2023, 2023010151. https://doi.org/10.20944/preprints202301.0151.v2
APA Style
Karabutov, N. (2023). Adaptive Parametric Identification of Systems with Multiple Nonlinearities. Preprints. https://doi.org/10.20944/preprints202301.0151.v2
Chicago/Turabian Style
Karabutov, N. 2023 "Adaptive Parametric Identification of Systems with Multiple Nonlinearities" Preprints. https://doi.org/10.20944/preprints202301.0151.v2
Abstract
The system identification problem with multiple nonlinearities is relevant. Its decision depends on many factors. These include: feedbacks, the method of connecting nonlinear links, signal properties. They affect the identifiability of the system parameters. We introduced a condition for the excitation constancy for state variables, which considers the S-identifiability of the system. We propose system decomposition by measuring input to identify parameters. Each subsystem has an implicit identification representation. It guarantees obtaining estimates of subsystem parameters based on experimental data. The trajectories boundedness of adaptive system proved in parametric and coordinate spaces. Conditions guaranteeing exponential stability of the system obtained. Systems of self-oscillation generation and nonlinear correction of a nonlinear system consider. Conditions for the trajectories boundedness of the adaptive system obtained for these cases. The influence of nonlinearity and feedback on the system performance estimated.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Nikolay Karabutov
Commenter's Conflict of Interests: Author