Hybrid State Estimation: Integrating Physics-Informed Neural Networks with Adaptive UKF for Dynamic Systems

https://doi.org/10.6084/m9.figshare.25970206

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posted on 2024-06-04, 18:54 authored by J. de CurtoJ. de Curto, I. de ZarzaI. de Zarza

<p dir="ltr">We introduce Python code designed to illustrate and apply key concepts in "Hybrid State Estimation: Integrating Physics-Informed Neural Networks with Adaptive UKF for Dynamic Systems".</p>

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The work is developed under the following projects at BARCELONA Supercomputing Center: `TIFON'. This work has also received funding from the `NEXTBAT' project funded by the EUROPEAN Union's HORIZON EUROPE research and innovation programme under grant agreement No. 101103983. The work is also developed under UFV R\&D pre-competitive project `OpenMaas: Open Manufacturing as a Service'.

Hybrid State Estimation: Integrating Physics-Informed Neural Networks with Adaptive UKF for Dynamic Systems

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