Ricarda-Samantha Götte

rgoette@hni.uni-paderborn.de
ID
43992

5 Publications

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[5]
2023 | Conference Paper | LibreCat-ID: 34171
Götte, R.-S., & Timmermann, J. (2023). Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 56(1), 85–90. https://doi.org/10.1016/j.ifacol.2023.02.015
LibreCat | DOI
 
[4]
2023 | Conference Paper | LibreCat-ID: 48482 | OA
Götte, R.-S., Klusmann, J. N., & Timmermann, J. (2023). Data-driven identification of disturbances using a sliding mode observer. Proceedings - 33. Workshop Computational Intelligence: Berlin, 23.-24. November 2023, 113–123. https://doi.org/10.5445/KSP/1000162754
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[3]
2023 | Conference Paper | LibreCat-ID: 44326
Götte, R.-S., & Timmermann, J. (2023). Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF. IFAC-PapersOnLine, 56(2), 869–874.
LibreCat
 
[2]
2022 | Conference Paper | LibreCat-ID: 26539 | OA
Götte, R.-S., & Timmermann, J. (2022). Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering. 2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC), 67–76. https://doi.org/10.1109/AIRC56195.2022.9836982
LibreCat | DOI | Download (ext.)
 
[1]
2022 | Conference Paper | LibreCat-ID: 31066
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
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5 Publications

Mark all

[5]
2023 | Conference Paper | LibreCat-ID: 34171
Götte, R.-S., & Timmermann, J. (2023). Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 56(1), 85–90. https://doi.org/10.1016/j.ifacol.2023.02.015
LibreCat | DOI
 
[4]
2023 | Conference Paper | LibreCat-ID: 48482 | OA
Götte, R.-S., Klusmann, J. N., & Timmermann, J. (2023). Data-driven identification of disturbances using a sliding mode observer. Proceedings - 33. Workshop Computational Intelligence: Berlin, 23.-24. November 2023, 113–123. https://doi.org/10.5445/KSP/1000162754
LibreCat | DOI | Download (ext.)
 
[3]
2023 | Conference Paper | LibreCat-ID: 44326
Götte, R.-S., & Timmermann, J. (2023). Approximating a Laplacian Prior for Joint State and Model Estimation within an UKF. IFAC-PapersOnLine, 56(2), 869–874.
LibreCat
 
[2]
2022 | Conference Paper | LibreCat-ID: 26539 | OA
Götte, R.-S., & Timmermann, J. (2022). Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering. 2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC), 67–76. https://doi.org/10.1109/AIRC56195.2022.9836982
LibreCat | DOI | Download (ext.)
 
[1]
2022 | Conference Paper | LibreCat-ID: 31066
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
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