| ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative–quantitative modeling S Streif, A Savchenko, P Rumschinski, S Borchers, R Findeisen Bioinformatics 28 (9), 1290-1291, 2012 | 43 | 2012 |
| Complete diagnosability of abrupt faults using set-based sensitivities A Savchenko, P Rumschinski, S Streif, R Findeisen Proc. 8th IFAC Symposium on Fault Detection, Supervision and Safety of …, 2012 | 17 | 2012 |
| Fault diagnosis for polynomial hybrid systems A Savchenko, P Rumschinski, R Findeisen Proc. IFAC World Congress, 2755-2760, 2011 | 15 | 2011 |
| Complete fault diagnosis of uncertain polynomial systems P Rumschinski, J Richter, A Savchenko, S Borchers, J Lunze, R Findeisen Proc. IFAC Symp. Dyn. Control Proc. Syst.(DyCoPs), 127-132, 2010 | 14 | 2010 |
| Towards nominal stability certification of deep learning-based controllers HH Nguyen, J Matschek, T Zieger, A Savchenko, N Noroozi, R Findeisen 2020 American Control Conference (ACC), 3886-3891, 2020 | 12 | 2020 |
| Towards Safe Neural Network Supported Model Predictive Control T Zieger, A Savchenko, T Oehlschlägel, R Findeisen IFAC-PapersOnLine 53 (2), 5246-5251, 2020 | 10 | 2020 |
| Controller verification and parametrization subject to quantitative and qualitative requirements P Andonov, A Savchenko, P Rumschinski, S Streif, R Findeisen Proc. of the International Symposium on Advanced Control of Chemical …, 2015 | 10 | 2015 |
| Improved Robust Predictive Control for Lur’e Systems Using Set-based Learning HH Nguyen, A Savchenko, S Yu, R Findeisen IFAC-PapersOnLine 51 (20), 487-492, 2018 | 8 | 2018 |
| Towards Risk-aware Machine Learning Supported Model Predictive Control and Open-loop Optimization for Repetitive Processes B Morabito, J Pohlodek, J Matschek, A Savchenko, L Carius, R Findeisen IFAC-PapersOnLine 54 (6), 321-328, 2021 | 7 | 2021 |
| Guaranteed Set-based Controller Parameter Estimation for Nonlinear Systems–Magnetic Levitation Platform as a Case Study A Savchenko, P Andonov, S Streif, R Findeisen IFAC World Congress, 2014 | 5 | 2014 |
| Stochastic model predictive control utilizing Bayesian neural networks J Pohlodek, H Alsmeier, B Morabito, C Schlauch, A Savchenko, ... 2023 American Control Conference (ACC), 603-608, 2023 | 4 | 2023 |
| Mathematical optimization and machine learning for efficient urban traffic J Bethge, R Findeisen, D Duc Le, M Merkert, S Sager, A Savchenko, ... German Success Stories in Industrial Mathematics, 113-120, 2022 | 4 | 2022 |
| High-Resolution Pixelwise Contact Area and Normal Force Estimation for the GelSight Mini Visuotactile Sensor Using Neural Networks N Funk, PO Müller, B Belousov, A Savchenko, R Findeisen, J Peters Embracing Contacts-Workshop at ICRA 2023, 2023 | 3 | 2023 |
| Efficient Set-based Process Monitoring and Fault Diagnosis A Savchenko Shaker Verlag Aachen, 2017 | 3 | 2017 |
| Structural problem reduction for set-based fault diagnosis A Savchenko, P Rumschinski, S Streif, R Findeisen Proc. IFAC Symp. Dyn. Contr. Proc. Syst.(DYCOPS), 860-865, 2013 | 3 | 2013 |
| One-Step Safe Neural Network Supported Control T Zieger, A Savchenko, T Oehlschlaegel, R Findeisen 2021 American Control Conference (ACC), 514-519, 2021 | 2 | 2021 |
| Admissible Control Parametrization of Uncertain Finite-time Processes With Application to Li-ion Battery Management P Andonov, B Morabito, A Savchenko, R Findeisen 2018 European Control Conference (ECC), 2338-2343, 2018 | 2 | 2018 |
| Multi-objective complexity reduction for set-based fault diagnosis A Savchenko, P Andonov, P Rumschinski, R Findeisen 2017 6th International Symposium on Advanced Control of Industrial Processes …, 2017 | 2 | 2017 |
| Extended Formulations for MINLP Problems by Value Decompositions UU Haus, D Michaels, A Savchenko Proceedings of the EngOpt 2008 conference, 2008 | 2 | 2008 |
| Controller Parametrization for Offset-free Control Using Set-Based Feasibility Methods P Andonov, A Savchenko, R Findeisen 2019 American Control Conference (ACC), 2795-2800, 2019 | 1 | 2019 |
Rolf FindeisenTU DarmstadtVerified email at iat.tu-darmstadt.de
