Köpeczi-Bócz, Ákos Tamás and Sykora, Henrik Tamás and Takács, Dénes (2023) Data-driven delay identification with SINDy. In: 3rd International Nonlinear Dynamics Conference, NODYCON, 2023.06.18-2023.06.22, Roma.
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Abstract
In this work, we investigate the capabilities of the Sparse Identification of Nonlinear Dynamics method for time-delay identification. A possible solution is shown how delayed terms can be introduced into the method. We test the robustness and effectiveness of the method through data generated by simulation of different reference systems with known time delay. Through our test examples, we investigate the effect of noise and the delay distribution in the candidate terms. We also test the method in the presence of multiple delays. It is shown that by iterating through a range of threshold values with the STLSQ algorithm, the delayed terms can be identified in a robust manner.
| Item Type: | Conference or Workshop Item (Paper) |
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| Uncontrolled Keywords: | Scientific Machine Learning, Sparse Identification of Nonlinear Dynamics, Time-delay identification |
| Subjects: | T Technology / alkalmazott, műszaki tudományok > TJ Mechanical engineering and machinery / gépészmérnöki tudományok |
| SWORD Depositor: | MTMT SWORD |
| Depositing User: | MTMT SWORD |
| Date Deposited: | 19 Sep 2023 11:27 |
| Last Modified: | 19 Sep 2023 11:27 |
| URI: | http://real.mtak.hu/id/eprint/173987 |
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