| Efficient model order reduction for multi-agent systems using QR decomposition-based clustering P Mlinarić, S Grundel, P Benner 54th IEEE Conference on Decision and Control (CDC), 4794 - 4799, 2015 | 29 | 2015 |
| Model reduction of linear multi-agent systems by clustering with and error bounds HJ Jongsma, P Mlinarić, S Grundel, P Benner, HL Trentelman Mathematics of Control, Signals, and Systems 30 (1), 2018 | 22 | 2018 |
| An ℋ2 ⊗ ℒ2‐Optimal Model Order Reduction Approach for Parametric Linear Time‐Invariant Systems M Hund, P Mlinarić, J Saak PAMM 18 (1), e201800084, 2018 | 14 | 2018 |
| Optimization-based Parametric Model Order Reduction via First-order Necessary Conditions M Hund, T Mitchell, P Mlinaric, J Saak SIAM Journal on Scientific Computing 44 (3), A1554-A1578, 2022 | 13 | 2022 |
| -Optimal Reduced-Order Modeling Using Parameter-Separable Forms P Mlinarić, S Gugercin SIAM Journal on Scientific Computing 45 (2), A554-A578, 2023 | 12 | 2023 |
| A Unifying Framework for Interpolatory -Optimal Reduced-Order Modeling P Mlinarić, S Gugercin SIAM Journal on Numerical Analysis 61 (5), 2133-2156, 2023 | 10 | 2023 |
| Synchronization and aggregation of nonlinear power systems with consideration of bus network structures P Mlinarić, T Ishizaki, A Chakrabortty, S Grundel, P Benner, J Imura 2018 European Control Conference (ECC), 2266-2271, 2018 | 8 | 2018 |
| Clustering-Based Model Order Reduction for Nonlinear Network Systems P Benner, S Grundel, P Mlinarić Model Reduction of Complex Dynamical Systems, 75-96, 2021 | 6 | 2021 |
| Structure-preserving model order reduction for network systems P Mlinarić | 6 | 2020 |
| Clustering-Based Model Order Reduction for Multi-Agent Systems with General Linear Time-Invariant Agents P Mlinarić, S Grundel, P Benner Proceedings of the 22nd International Symposium on Mathematical Theory of …, 2016 | 5 | 2016 |
| System‐theoretic model order reduction with pyMOR L Balicki, P Mlinarić, S Rave, J Saak PAMM 19 (1), e201900459, 2019 | 3 | 2019 |
| Parametric Model Order Reduction Using pyMOR P Mlinarić, S Rave, J Saak Model Reduction of Complex Dynamical Systems, 357-367, 2021 | 2 | 2021 |
| IRKA is a Riemannian Gradient Descent Method P Mlinarić, CA Beattie, Z Drmač, S Gugercin IEEE Transactions on Automatic Control, 2024 | 1 | 2024 |
| Interpolatory Necessary Optimality Conditions for Reduced-order Modeling of Parametric Linear Time-invariant Systems P Mlinarić, P Benner, S Gugercin arXiv preprint arXiv:2401.10047, 2024 | 1 | 2024 |
| Interpolatory -optimality Conditions for Structured Linear Time-invariant Systems P Mlinarić, P Benner, S Gugercin arXiv preprint arXiv:2310.10618, 2023 | | 2023 |
| A Unifying Framework for Interpolatory -optimal Reduced-order Modeling P Mlinarić, S Gugercin arXiv preprint arXiv:2209.00714, 2022 | | 2022 |
| -optimal Reduced-order Modeling Using Parameter-separable Forms P Mlinarić, S Gugercin arXiv preprint arXiv:2206.02929, 2022 | | 2022 |
| Model Reduction of Linear Multi-Agent Systems by Clustering and Associated - and -Error Bounds HJ Jongsma, P Mlinarić, S Grundel, P Benner, HL Trentelman arXiv preprint arXiv:1610.02432, 2016 | | 2016 |
| Stability preserving model reduction for linearly coupled linear time‐invariant systems P Benner, S Grundel, P Mlinarić PAMM 16 (1), 817-818, 2016 | | 2016 |
| Aproksimacija linearnih dinamičkih sistema u prostoru P Mlinarić University of Zagreb. Faculty of Science. Department of Mathematics., 2014 | | 2014 |
Peter BennerMax Planck Institute for Dynamics of Complex Technical SystemsVerified email at mpi-magdeburg.mpg.de
