{"page":"19-24","abstract":[{"lang":"eng","text":"While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model. "}],"publication":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","_id":"31066","year":"2022","volume":55,"issue":"12","quality_controlled":"1","citation":{"chicago":"Schön, Oliver, Ricarda-Samantha Götte, and Julia Timmermann. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” In 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55:19–24, 2022. https://doi.org/10.1016/j.ifacol.2022.07.282.","short":"O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.","ama":"Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022). Vol 55. ; 2022:19-24. doi:https://doi.org/10.1016/j.ifacol.2022.07.282","apa":"Schön, O., Götte, R.-S., & Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24. https://doi.org/10.1016/j.ifacol.2022.07.282","mla":"Schön, Oliver, et al. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), vol. 55, no. 12, 2022, pp. 19–24, doi:https://doi.org/10.1016/j.ifacol.2022.07.282.","ieee":"O. Schön, R.-S. Götte, and J. Timmermann, “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems,” in 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), Casablanca, Morocco, 2022, vol. 55, no. 12, pp. 19–24, doi: https://doi.org/10.1016/j.ifacol.2022.07.282.","bibtex":"@inproceedings{Schön_Götte_Timmermann_2022, title={Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}, volume={55}, DOI={https://doi.org/10.1016/j.ifacol.2022.07.282}, number={12}, booktitle={14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)}, author={Schön, Oliver and Götte, Ricarda-Samantha and Timmermann, Julia}, year={2022}, pages={19–24} }"},"keyword":["neural networks","physics-guided","data-driven","multi-objective optimization","system identification","machine learning","dynamical systems"],"user_id":"43992","doi":"https://doi.org/10.1016/j.ifacol.2022.07.282","department":[{"_id":"153"},{"_id":"880"}],"language":[{"iso":"eng"}],"author":[{"last_name":"Schön","full_name":"Schön, Oliver","first_name":"Oliver"},{"last_name":"Götte","first_name":"Ricarda-Samantha","id":"43992","full_name":"Götte, Ricarda-Samantha"},{"last_name":"Timmermann","first_name":"Julia","full_name":"Timmermann, Julia","id":"15402"}],"title":"Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems","status":"public","date_updated":"2024-11-13T08:43:16Z","conference":{"name":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","start_date":"2022-06-29","end_date":"2022-07-01","location":"Casablanca, Morocco"},"type":"conference","date_created":"2022-05-05T06:22:55Z","intvolume":" 55"}