Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering

R.-S. Götte, J. Timmermann, in: AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control, 2022.

Conference Paper | English
Abstract
In control design most control strategies are model-based and require accurate models to be applied successfully. Due to simplifications and the model-reality-gap physics-derived models frequently exhibit deviations from real-world-systems. Likewise, purely data-driven methods often do not generalise well enough and may violate physical laws. Recently Physics-Guided Neural Networks (PGNN) and physics-inspired loss functions separately have shown promising results to conquer these drawbacks. In this contribution we extend existing methods towards the identification of non-autonomous systems and propose a combined approach PGNN-L, which uses a PGNN and a physics-inspired loss term (-L) to successfully identify the system's dynamics, while maintaining the consistency with physical laws. The proposed method is demonstrated on two real-world nonlinear systems and outperforms existing techniques regarding complexity and reliability.
Publishing Year
Proceedings Title
AIRC'22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control
Conference
3rd International Conference on Artificial Intelligence, Robotics and Control
Conference Location
Cairo, Egypt
Conference Date
2021-12-08 – 2021-12-10
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Cite this

Götte R-S, Timmermann J. Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering. In: AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control. ; 2022.
Götte, R.-S., & Timmermann, J. (2022). Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering. AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control. 3rd International Conference on Artificial Intelligence, Robotics and Control, Cairo, Egypt.
@inproceedings{Götte_Timmermann_2022, title={Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering}, booktitle={AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control}, author={Götte, Ricarda-Samantha and Timmermann, Julia}, year={2022} }
Götte, Ricarda-Samantha, and Julia Timmermann. “Composed Physics- and Data-Driven System Identification for Non-Autonomous Systems in Control Engineering.” In AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control, 2022.
R.-S. Götte and J. Timmermann, “Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering,” presented at the 3rd International Conference on Artificial Intelligence, Robotics and Control, Cairo, Egypt, 2022.
Götte, Ricarda-Samantha, and Julia Timmermann. “Composed Physics- and Data-Driven System Identification for Non-Autonomous Systems in Control Engineering.” AIRC’22: 2022 3rd International Conference on Artificial Intelligence, Robotics and Control, 2022.
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