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2020 – today
- 2025
[i39]Hendrik Alsmeier, Lukas Theiner, Anton Savchenko, Ali Mesbah, Rolf Findeisen:
Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification. CoRR abs/2501.03671 (2025)- 2024
- [j39]Joachim Schaeffer
, Eric Lenz, William C. Chueh, Martin Z. Bazant, Rolf Findeisen, Richard D. Braatz:
Interpretation of high-dimensional linear regression: Effects of nullspace and regularization demonstrated on battery data. Comput. Chem. Eng. 180: 108471 (2024) - [j38]Cheng Jiang, Xue Li, Dajun Du, Lei Wu, Rolf Findeisen:
Cross-Domain Authentication Scheme Based on Distributed Two-Layer Collaborative Blockchains for Cyber-Physical Power Systems. IEEE Internet Things J. 11(10): 17468-17481 (2024) - [j37]Jun Fu, Yanhui Liu, Rolf Findeisen, Tianyou Chai:
Model Predictive Control With Guaranteed Feasibility of Inequality Path Constraints. IEEE Trans. Cybern. 54(12): 7767-7779 (2024) - [c134]Joachim Schaeffer, Giacomo Galuppini, Jinwook Rhyu, Patrick A. Asinger, Robin Droop, Rolf Findeisen, Richard D. Braatz:
Cycle Life Prediction for Lithium-ion Batteries: Machine Learning and More. ACC 2024: 763-768 - [c133]Hendrik Alsmeier, Anton Savchenko, Rolf Findeisen:
Neural Horizon Model Predictive Control - Increasing Computational Efficiency with Neural Networks. ACC 2024: 1646-1651 - [c132]Maik Pfefferkorn, Venkatraman Renganathan, Rolf Findeisen:
Regret and Conservatism of Distributionally Robust Constrained Stochastic Model Predictive Control. ACC 2024: 3251-3257 - [c131]Minsu Kim, Joachim Schaeffer, Marc D. Berliner, Berta Pedret Sagnier, Rolf Findeisen, Richard D. Braatz:
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries. ACC 2024: 5339-5344 - [c130]Keivan Ahmadi, Rudolph L. Kok, Rolf Findeisen:
Surrogate Model Supported Optimization of high-definition Temporal Interference Stimulation. BioCAS 2024: 1-5 - [c129]Philipp Holzmann, Maik Pfefferkorn, Jan Peters, Rolf Findeisen:
Learning Energy-Efficient Trajectory Planning for Robotic Manipulators Using Bayesian Optimization. ECC 2024: 1374-1379 - [c128]Tingzhong Fu, Hoang Hai Nguyen, Rolf Findeisen:
Guaranteed Collision Avoidance for Autonomous Vehicles Fusing Model Predictive Control and Data Driven Reachability Analysis. ECC 2024: 2286-2291 - [c127]Roland Schurig, Andreas Himmel, Rolf Findeisen:
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees. ECC 2024: 3164-3170 - [c126]Mohamed Soliman, Rolf Findeisen:
Moving Horizon Planning and Control for Autonomous Vehicles with Active Exploration and Fallback Strategies. ICINCO (1) 2024: 359-367 - [i38]Sebastián Espinel-Ríos, Gerrich Behrendt, Jasmin Bauer, Bruno Morabito, Johannes Pohlodek, Andrea Schütze, Rolf Findeisen, Katja Bettenbrock, Steffen Klamt:
Experimentally implemented dynamic optogenetic optimization of ATPase expression using knowledge-based and Gaussian-process-supported models. CoRR abs/2401.08556 (2024) - [i37]Joachim Schaeffer, Giacomo Galuppini, Jinwook Rhyu, Patrick A. Asinger, Robin Droop, Rolf Findeisen, Richard D. Braatz:
Cycle Life Prediction for Lithium-ion Batteries: Machine Learning and More. CoRR abs/2404.04049 (2024) - [i36]Sebastian Hirt, Andreas Höhl, Joachim Schaeffer, Johannes Pohlodek, Richard D. Braatz, Rolf Findeisen:
Learning Model Predictive Control Parameters via Bayesian Optimization for Battery Fast Charging. CoRR abs/2404.06125 (2024) - [i35]Sebastian Hirt, Maik Pfefferkorn, Ali Mesbah, Rolf Findeisen:
Stability-informed Bayesian Optimization for MPC Cost Function Learning. CoRR abs/2404.12187 (2024) - [i34]Minsu Kim, Joachim Schaeffer, Marc D. Berliner, Berta Pedret Sagnier, Rolf Findeisen, Richard D. Braatz:
Accounting for the Effects of Probabilistic Uncertainty During Fast Charging of Lithium-ion Batteries. CoRR abs/2405.01681 (2024) - [i33]Joachim Schaeffer, Eric Lenz, Duncan Gulla, Martin Z. Bazant, Richard D. Braatz, Rolf Findeisen:
Lithium-Ion Battery System Health Monitoring and Fault Analysis from Field Data Using Gaussian Processes. CoRR abs/2406.19015 (2024) - [i32]Hendrik Alsmeier, Anton Savchenko, Rolf Findeisen:
Neural Horizon Model Predictive Control - Increasing Computational Efficiency with Neural Networks. CoRR abs/2408.09781 (2024) - [i31]Sebastian Hirt, Maik Pfefferkorn, Rolf Findeisen:
Safe and Stable Closed-Loop Learning for Neural-Network-Supported Model Predictive Control. CoRR abs/2409.10171 (2024) - [i30]Sebastian Hirt, Andreas Höhl, Johannes Pohlodek, Joachim Schaeffer, Maik Pfefferkorn, Richard D. Braatz, Rolf Findeisen:
Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging. CoRR abs/2410.04982 (2024) - [i29]Alexander Rose, Philipp Schaub, Rolf Findeisen:
Safe and High-Performance Learning of Model Predicitve Control using Kernel-Based Interpolation. CoRR abs/2410.06771 (2024) - [i28]Maik Pfefferkorn, Rolf Findeisen:
Probabilistically Input-to-State Stable Stochastic Model Predictive Control. CoRR abs/2410.08186 (2024) - [i27]Joachim Schaeffer, Jinwook Rhyu, Robin Droop, Rolf Findeisen, Richard D. Braatz:
Interpretation of High-Dimensional Regression Coefficients by Comparison with Linearized Compressing Features. CoRR abs/2411.12060 (2024) - [i26]Sebastian Hirt, Lukas Theiner, Rolf Findeisen:
Time-Series-Informed Closed-loop Learning for Sequential Decision Making and Control. CoRR abs/2412.02423 (2024) - 2023
- [j36]Roland Schurig, Andreas Himmel, Rolf Findeisen:
Toward Grassmannian Dimensionality Reduction in MPC. IEEE Control. Syst. Lett. 7: 3187-3192 (2023) - [j35]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
A Polynomial Chaos Approach to Robust Static Output-Feedback Control With Bounded Truncation Error. IEEE Trans. Autom. Control. 68(1): 470-477 (2023) - [j34]Janine Matschek, Johanna Bethge, Rolf Findeisen:
Safe Machine-Learning-Supported Model Predictive Force and Motion Control in Robotics. IEEE Trans. Control. Syst. Technol. 31(6): 2380-2392 (2023) - [j33]Jun Fu, Junfei Qiao, Kok Lay Teo, Rolf Findeisen:
Guest Editorial: Special Issue on Theory, Algorithms, and Applications for Hybrid Intelligent Dynamic Optimization. IEEE Trans. Neural Networks Learn. Syst. 34(9): 5231-5233 (2023) - [c125]Johannes Pohlodek, Hendrik Alsmeier, Bruno Morabito, Christian Schlauch, Anton Savchenko, Rolf Findeisen:
Stochastic Model Predictive Control Utilizing Bayesian Neural Networks. ACC 2023: 603-608 - [c124]Janine Matschek, Marc D. Berliner, Andreas Himmel, Richard D. Braatz, Rolf Findeisen:
Necessary Optimality Conditions for Fast Lithium-ion Battery Charging via Hybrid Simulations. ACC 2023: 3783-3789 - [c123]Roland Schurig, Andreas Himmel, Amer Mesanovic, Richard D. Braatz, Rolf Findeisen:
Estimating Parameter Regions for Structured Parameter Tuning via Reduced Order Subsystem Models. ACC 2023: 3809-3814 - [c122]Andreas Höhl, Michael Maiworm, Rolf Findeisen:
Path Following or Tracking Model Predictive Control for Towing Kites - A Question of Formulation or Learning? CCTA 2023: 459-465 - [c121]Felix Häusser, Andreas Himmel, Kai S. Karvinen, Rolf Findeisen:
Data-driven Adaptive Surface Control for Automated Directional Drilling. CCTA 2023: 520-525 - [c120]Alexander Rose, Maik Pfefferkorn, Hoang Hai Nguyen, Rolf Findeisen:
Learning a Gaussian Process Approximation of a Model Predictive Controller with Guarantees. CDC 2023: 4094-4099 - [c119]Bahaaeldin Elsayed, Mohamed Ibrahim, Rolf Findeisen:
Moving Horizon Planning and Control Under Uncertainties with Guarantees - Combining Operational Choices and Motion Primitives. CoDIT 2023: 2384-2389 - [c118]Bahaaeldin Elsayed, Rolf Findeisen:
Generic Motion Primitives-based Safe Motion Planner under Uncertainty for Autonomous Navigation in Cluttered Environments. ICAT 2023: 1-6 - [c117]Bahaaeldin Elsayed, Rolf Findeisen:
Trajectory Planning for Multiple Vehicles Using Motion Primitives: A Moving Horizon Approach Under Uncertainty. ICINCO (1) 2023: 229-236 - [c116]Felix Laub, Christoph Haugwitz, Gianni Allevato, Julian Seiler, Rolf Findeisen, Mario Kupnik:
Non-Contact Lamb Wave Defect Detection Based Solely on Air-Coupled Ultrasonic Phased Arrays. SENSORS 2023: 1-4 - [i25]Andreas Himmel, Janine Matschek, Rudolph Kok, Bruno Morabito, Hoang Hai Nguyen, Rolf Findeisen:
Machine Learning for Process Control of (Bio)Chemical Processes. CoRR abs/2301.06073 (2023) - [i24]Sebastián Espinel-Ríos, Bruno Morabito, Johannes Pohlodek, Katja Bettenbrock, Steffen Klamt, Rolf Findeisen:
Towards a modeling, optimization and predictive control framework for fed-batch metabolic cybergenetics. CoRR abs/2302.02177 (2023) - [i23]Joachim Schaeffer, Paul Gasper, Esteban García Tamayo, Raymond Gasper, Masaki Adachi, Juan Pablo Gaviria-Cardona, Simon Montoya-Bedoya, Anoushka Bhutani, Andrew Schiek, Rhys Goodall, Rolf Findeisen, Richard D. Braatz, Simon Engelke:
Machine learning benchmarks for the classification of equivalent circuit models from solid-state electrochemical impedance spectra. CoRR abs/2302.03362 (2023) - [i22]Janine Matschek, Johanna Bethge, Rolf Findeisen:
Safe Machine-Learning-supported Model Predictive Force and Motion Control in Robotics. CoRR abs/2303.04569 (2023) - [i21]Johanna Bethge, Maik Pfefferkorn, Alexander Rose, Jan Peters, Rolf Findeisen:
Model Predictive Control with Gaussian-Process-Supported Dynamical Constraints for Autonomous Vehicles. CoRR abs/2303.04725 (2023) - [i20]Hoang Hai Nguyen, Maurice Friedel, Rolf Findeisen:
LMI-based Data-Driven Robust Model Predictive Control. CoRR abs/2303.04777 (2023) - [i19]Johannes Pohlodek, Hendrik Alsmeier, Bruno Morabito, Christian Schlauch, Anton Savchenko, Rolf Findeisen:
Stochastic Model Predictive Control Utilizing Bayesian Neural Networks. CoRR abs/2303.14519 (2023) - [i18]Joachim Schaeffer, Eric Lenz, William C. Chueh, Martin Z. Bazant, Rolf Findeisen, Richard D. Braatz:
Interpretation of High-Dimensional Linear Regression: Effects of Nullspace and Regularization Demonstrated on Battery Data. CoRR abs/2309.00564 (2023) - [i17]Maik Pfefferkorn, Venkatraman Renganathan, Rolf Findeisen:
Regret and Conservatism of Constrained Stochastic Model Predictive Control. CoRR abs/2309.12190 (2023) - [i16]Roland Schurig, Andreas Himmel, Rolf Findeisen:
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees. CoRR abs/2312.02734 (2023) - 2022
- [j32]Hoang Hai Nguyen, Maik Pfefferkorn, Rolf Findeisen:
High-probability stable Gaussian process-supported model predictive control for Lur'e systems. Eur. J. Control 68: 100695 (2022) - [j31]Amer Mesanovic, Ulrich Münz, Rolf Findeisen:
Scalable and Data Privacy Conserving Controller Tuning for Large-Scale Power Networks. IEEE Trans. Control. Syst. Technol. 30(2): 696-711 (2022) - [c115]Bruno Morabito, Hoang Hai Nguyen, Janine Matschek, Rolf Findeisen:
Safe Exploration Learning Supported Model Predictive Control of Repetitive Processes. ACC 2022: 2631-2636 - [c114]Christina Eckel, Michael Maiworm, Rolf Findeisen:
Optimal Operation and Control of Towing Kites using Online and Offline Gaussian Process Learning Supported Model Predictive Control. ACC 2022: 2637-2643 - [c113]Maik Pfefferkorn, Michael Maiworm, Rolf Findeisen:
Exact Multiple-Step Predictions in Gaussian Process-based Model Predictive Control: Observations, Possibilities, and Challenges. ACC 2022: 2829-2836 - [c112]Tim Zieger, Hoang Hai Nguyen, Erik Schulz, Thimo Oehlschlägel, Rolf Findeisen:
Non-diverging neural networks supported tube model predictive control. CDC 2022: 3066-3073 - [c111]Philipp Holzmann, Janine Matschek, Maik Pfefferkorn, Rolf Findeisen:
Learning secure corridors for model predictive path following control of autonomous systems in cluttered environments. ECC 2022: 1772-1777 - [i15]Johannes Pohlodek, Bruno Morabito, Christian Schlauch, Pablo Zometa, Rolf Findeisen:
Flexible development and evaluation of machine-learning-supported optimal control and estimation methods via HILO-MPC. CoRR abs/2203.13671 (2022) - [i14]Markus Koegel, Mohamed Ibrahim, Christian Kallies, Rolf Findeisen:
Safe Hierarchical Model Predictive Control and Planning for Autonomous Systems. CoRR abs/2203.14269 (2022) - 2021
- [j30]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
Polynomial chaos-based H2 output-feedback control of systems with probabilistic parametric uncertainties. Autom. 131: 109743 (2021) - [c110]Tim Zieger, Anton Savchenko, Thimo Oehlschlägel, Rolf Findeisen:
One-Step Safe Neural Network Supported Control. ACC 2021: 514-519 - [c109]Markus J. Kögel, Rolf Findeisen:
Reducing conservatism in stochastic model predictive blending multiple control gains. ACC 2021: 2094-2101 - [c108]Hoang Hai Nguyen, Tim Zieger, Sandra C. Wells, Anastasia Nikolakopoulou, Richard D. Braatz, Rolf Findeisen:
Stability Certificates for Neural Network Learning-based Controllers using Robust Control Theory. ACC 2021: 3564-3569 - [c107]Markus J. Kögel, Rolf Findeisen:
Robust output feedback MPC with reduced conservatism for linear uncertain systems using time varying tubes. CDC 2021: 2571-2577 - [i13]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
A Polynomial Chaos Approach to Robust H∞ Static Output-Feedback Control with Bounded Truncation Error. CoRR abs/2102.08626 (2021) - [i12]Michael Maiworm, Christian Wagner, Taner Esat, Philipp Leinen, Ruslan Temirov, Rolf Findeisen, F. Stefan Tautz:
Control of Scanning Quantum Dot Microscopy. CoRR abs/2102.12708 (2021) - [i11]Joe Watson, Hany Abdulsamad, Rolf Findeisen, Jan Peters:
Stochastic Control through Approximate Bayesian Input Inference. CoRR abs/2105.07693 (2021) - 2020
- [j29]Armin Nurkanovic, Amer Mesanovic, Mario Sperl, Sebastian Albrecht, Ulrich Münz, Rolf Findeisen, Moritz Diehl:
Optimization-based primary and secondary control of microgrids. Autom. 68(12): 1044-1058 (2020) - [j28]Banafsheh Jabarivelisdeh, Lisa Carius, Rolf Findeisen, Steffen Waldherr:
Adaptive predictive control of bioprocesses with constraint-based modeling and estimation. Comput. Chem. Eng. 135: 106744 (2020) - [j27]Tillmann Mühlpfordt, Rolf Findeisen, Veit Hagenmeyer, Timm Faulwasser:
Errata for "Comments on Truncation Errors for Polynomial Chaos Expansions". IEEE Control. Syst. Lett. 4(2): 504-505 (2020) - [j26]Gustavo Hernandez-Mejia, Alma Y. Alanis, Miguel Hernández-González, Rolf Findeisen, Esteban A. Hernández-Vargas:
Passivity-Based Inverse Optimal Impulsive Control for Influenza Treatment in the Host. IEEE Trans. Control. Syst. Technol. 28(1): 94-105 (2020) - [c106]Johanna Bethge, Shuyou Yu, Rolf Findeisen:
Model predictive control with guarantees for discrete linear stochastic systems subject to additive disturbances with chance constraints. ACC 2020: 1943-1948 - [c105]Markus J. Kögel, Rolf Findeisen:
Robust MPC with Reduced Conservatism Blending Multiples Tubes. ACC 2020: 1949-1954 - [c104]Hoang Hai Nguyen, Janine Matschek, Tim Zieger, Anton Savchenko, Navid Noroozi, Rolf Findeisen:
Towards nominal stability certification of deep learning-based controllers. ACC 2020: 3886-3891 - [c103]Petar Andonov, Anton Savchenko, Philipp Rumschinski, Thomas Trenner, Jörg Neidig, Rolf Findeisen:
Monitoring and verification of event-driven transportation systems in discrete manufacturing. CCTA 2020: 1-7 - [c102]Janine Matschek, Reni Jordanowa, Rolf Findeisen:
Direct Force Feedback using Gaussian Process based Model Predictive Control. CCTA 2020: 8-13 - [c101]Maik Pfefferkorn, Michael Maiworm, Christian Wagner, F. Stefan Tautz, Rolf Findeisen:
Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy. CDC 2020: 5525-5531 - [c100]Mohamed Ibrahim, Christian Kallies, Rolf Findeisen:
Learning-Supported Approximated Optimal Control for Autonomous Vehicles in the Presence of State Dependent Uncertainties. ECC 2020: 338-343 - [c99]Janine Matschek, Tim Gonschorek, Magnus Hanses, Norbert Elkmann, Frank Ortmeier, Rolf Findeisen:
Learning References with Gaussian Processes in Model Predictive Control applied to Robot Assisted Surgery. ECC 2020: 362-367 - [c98]Lingyu Meng, Shuyou Yu, Huan Chang, Rolf Findeisen, Hong Chen:
Path following and terminal force control of robotic manipulators. ICCA 2020: 1482-1487 - [c97]Janine Matschek, Rolf Findeisen:
Learning supported Model Predictive Control for Tracking of Periodic References. L4DC 2020: 511-520 - [i10]Maik Pfefferkorn, Michael Maiworm, Christian Wagner, F. Stefan Tautz, Rolf Findeisen:
Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy. CoRR abs/2004.02488 (2020) - [i9]Amer Mesanovic, Ulrich Münz, Rolf Findeisen:
Controller tuning in power systems using singular value optimization. CoRR abs/2005.03949 (2020)
2010 – 2019
- 2019
- [j25]Henning Lindhorst, Sergio Lucia, Rolf Findeisen, Steffen Waldherr:
Modeling Enzyme Controlled Metabolic Networks in Rapidly Changing Environments by Robust Optimization. IEEE Control. Syst. Lett. 3(2): 248-253 (2019) - [c96]Stefano Di Cairano, Tobias Bäthge, Rolf Findeisen:
Modular Design for Constrained Control of Actuator-Plant Cascades. ACC 2019: 1755-1760 - [c95]Petar Andonov, Anton Savchenko, Rolf Findeisen:
Controller Parametrization for Offset-free Control Using Set-Based Feasibility Methods. ACC 2019: 2795-2800 - [c94]Markus J. Kögel, Rolf Findeisen:
Combined online communication scheduling and output feedback MPC of cyber-physical systems. CCNC 2019: 1-6 - [c93]Seyed Hossein Mousavi, Navid Noroozi, Roman Geiselhart, Markus J. Kögel, Rolf Findeisen:
On integral input-to-state stability of event-triggered control systems. CDC 2019: 1674-1679 - [c92]Navid Noroozi, Roxanne Jackson, Daniel E. Quevedo, Fabian R. Wirth, Rolf Findeisen:
On noise-to-state stability of stochastic discrete-time systems via finite-step Lyapunov functions. CDC 2019: 5406-5411 - [c91]Markus J. Kögel, Daniel E. Quevedo, Rolf Findeisen:
Combined control and communication scheduling for constrained system using robust output feedback MPC. ECC 2019: 1778-1783 - [i8]Amer Mesanovic, Ulrich Münz, Andrei Szabo, Martin Mangold, Joachim Bamberger, Michael Metzger, Chris Heyde, Rainer Krebs, Rolf Findeisen:
Guaranteed H-infinity Controller Parameter Tuning for Power Systems: Method and Experimental Evaluation. CoRR abs/1910.12335 (2019) - [i7]Amer Mesanovic, Ulrich Münz, Rolf Findeisen:
Scalable and Data Privacy Conserving Controller Tuning for Large-Scale Power Networks. CoRR abs/1911.01499 (2019) - [i6]Michael Maiworm, Daniel Limón, Rolf Findeisen:
Online Gaussian Process learning-based Model Predictive Control with Stability Guarantees. CoRR abs/1911.03315 (2019) - [i5]Janine Matschek, Tim Gonschorek, Magnus Hanses, Norbert Elkmann, Frank Ortmeier, Rolf Findeisen:
Learning References with Gaussian Processes in Model Predictive Control applied to Robot Assisted Surgery. CoRR abs/1911.10793 (2019) - 2018
- [j24]Rolf Findeisen, Knut Graichen, Martin Mönnigmann:
Eingebettete Optimierung in der Regelungstechnik - Grundlagen und Herausforderungen. Autom. 66(11): 877-902 (2018) - [j23]Sergio Lucia, Denis Navarro, Oscar Lucía, Pablo Zometa, Rolf Findeisen:
Optimized FPGA Implementation of Model Predictive Control for Embedded Systems Using High-Level Synthesis Tool. IEEE Trans. Ind. Informatics 14(1): 137-145 (2018) - [c90]Michael Kopf, Eric Bullinger, Hans-Gerd Giesseler, Stephan Adden, Rolf Findeisen:
Model Predictive Control for Aircraft Load Alleviation: Opportunities and Challenges. ACC 2018: 2417-2424 - [c89]Khalid J. Kazim, Johanna Bethge, Janine Matschek, Rolf Findeisen:
Combined Predictive Path Following and Admittance Control. ACC 2018: 3153-3158 - [c88]Amer Mesanovic, Dominik Unseld, Ulrich Münz, Christian Ebenbauer, Rolf Findeisen:
Parameter Tuning and Optimal Design of Decentralized Structured Controllers for Power Oscillation Damping in Electrical Networks. ACC 2018: 3828-3833 - [c87]Michael Maiworm, Christian Wagner, Ruslan Temirov, F. Stefan Tautz, Rolf Findeisen:
Two-degree-of-freedom control combining machine learning and extremum seeking for fast scanning quantum dot microscopy. ACC 2018: 4360-4366 - [c86]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
Robust Static H∞ Output-Feedback Control Using Polynomial Chaos. ACC 2018: 6804-6809 - [c85]Markus J. Kögel, Rolf Findeisen:
Improved Robust Decentralized MPC. ECC 2018: 312-318 - [c84]Markus J. Kögel, Petar Andonov, Marco Filax, Frank Ortmeier, Rolf Findeisen:
Predictive Tracking Control of a Camera - Head Mounted Display System subject to Communication Constraints. ECC 2018: 1035-1041 - [c83]Petar Andonov, Bruno Morabito, Anton Savchenko, Rolf Findeisen:
Admissible Control Parametrization of Uncertain Finite-time Processes With Application to Li-ion Battery Management. ECC 2018: 2338-2343 - [c82]Amer Mesanovic, Ulrich Münz, Joachim Bamberger, Rolf Findeisen:
Controller Tuning for the Improvement of Dynamic Security in Power Systems. ISGT Europe 2018: 1-6 - 2017
- [j22]Timm Faulwasser, Tobias Weber, Pablo Zometa, Rolf Findeisen:
Implementation of Nonlinear Model Predictive Path-Following Control for an Industrial Robot. IEEE Trans. Control. Syst. Technol. 25(4): 1505-1511 (2017) - [c81]Masako Kishida, Markus J. Kögel, Rolf Findeisen:
Event-triggered actuator signal update using self-triggered sampled data for uncertain linear systems. ACC 2017: 3035-3041 - [c80]Bruno Morabito, Reinhardt Klein, Rolf Findeisen:
Real time feasibility and performance of moving horizon estimation for Li-ion batteries based on first principles electrochemical models. ACC 2017: 3457-3462 - [c79]Sergio Lucia, Marcello Torchio, Davide Martino Raimondo, Reinhardt Klein, Richard D. Braatz, Rolf Findeisen:
Towards adaptive health-aware charging of Li-ion batteries: A real-time predictive control approach using first-principles models. ACC 2017: 4717-4722 - [c78]Sergio Lucia, Joel A. Paulson, Rolf Findeisen, Richard D. Braatz:
On stability of stochastic linear systems via polynomial chaos expansions. ACC 2017: 5089-5094 - [c77]Markus J. Kögel, Rolf Findeisen:
Low latency output feedback model predictive control for constrained linear systems. CDC 2017: 1925-1932 - [c76]Amer Mesanovic, Ulrich Münz, Rolf Findeisen:
Coordinated tuning of synchronous generator controllers for power oscillation damping. ISGT Europe 2017: 1-6 - [i4]Tillmann Mühlpfordt, Rolf Findeisen, Veit Hagenmeyer, Timm Faulwasser:
Comments on Truncation Errors for Polynomial Chaos Expansions. CoRR abs/1708.07655 (2017) - 2016
- [j21]Sergio Lucia, Markus J. Kögel, Pablo Zometa, Daniel E. Quevedo, Rolf Findeisen:
Predictive control, embedded cyberphysical systems and systems of systems - A perspective. Annu. Rev. Control. 41: 193-207 (2016) - [j20]Timm Faulwasser, Rolf Findeisen:
Nonlinear Model Predictive Control for Constrained Output Path Following. IEEE Trans. Autom. Control. 61(4): 1026-1039 (2016) - [c75]Tillmann Muhlpfordt, Joel A. Paulson, Richard D. Braatz, Rolf Findeisen:
Output feedback model predictive control with probabilistic uncertainties for linear systems. ACC 2016: 2035-2040 - [c74]Rolf Findeisen, Martha A. Grover, Christian Wagner, Michael Maiworm, Ruslan Temirov, F. Stefan Tautz, Murti V. Salapaka, Srinivasa M. Salapaka, Richard D. Braatz, S. O. Reza Moheimani:
Control on a molecular scale: A perspective. ACC 2016: 3069-3082 - [c73]Michael Maiworm, Christian Wagner, F. Stefan Tautz, Rolf Findeisen:
Manipulation on a molecular level: towards controlled molecular 3D printing. ACC 2016: 3094 - [c72]Shuyou Yu, Ting Qu, Rolf Findeisen, Hong Chen:
Model predictive control for uncertain nonlinear systems subject to chance constraints. CDC 2016: 2751-2756 - [c71]Tobias Bäthge, Sergio Lucia, Rolf Findeisen:
Exploiting models of different granularity in robust predictive control. CDC 2016: 2763-2768 - [c70]Masako Kishida, Markus J. Kögel, Rolf Findeisen:
Verifying robust forward admissibility for nonlinear systems using (skewed) structured singular values. CDC 2016: 4065-4071 - [c69]Pablo Zometa, Hannes Heinemann, Sergio Lucia, Markus J. Kögel, Rolf Findeisen:
Efficient stochastic model predictive control for embedded systems based on second-order cone programs. ECC 2016: 166-171 - [c68]Gergely Takács, Pablo Zometa, Rolf Findeisen, Boris Rohal-Ilkiv:
Efficiency and performance of embedded model predictive control for active vibration attenuation. ECC 2016: 1334-1340 - 2015
- [c67]Ion Necoara, Rolf Findeisen:
Parallel and distributed random coordinate descent method for convex error bound minimization. ACC 2015: 527-532 - [c66]Markus J. Kögel, Rolf Findeisen:
Discrete-time robust model predictive control for continuous-time nonlinear systems. ACC 2015: 924-930 - [c65]Michael Kopf, Hans-Gerd Giesseler, Paolo Varutti, Timm Faulwasser, Rolf Findeisen:
On the effect of enforcing stability in model predictive control for gust load alleviation. ACC 2015: 2329-2334 - [c64]Sergio Lucia, Pablo Zometa, Markus J. Kögel, Rolf Findeisen:
Efficient stochastic model predictive control based on polynomial chaos expansions for embedded applications. CDC 2015: 3006-3012 - [c63]Andrei Patrascu, Ion Necoara, Rolf Findeisen:
Rate of convergence analysis of a dual fast gradient method for general convex optimization. CDC 2015: 3311-3316 - [c62]Markus J. Kögel, Rolf Findeisen:
Robust output feedback predictive control with self-triggered measurements. CDC 2015: 5487-5493 - [c61]Masako Kishida, Rolf Findeisen:
μ-based approaches to determining guaranteed consistent and inconsistent parameter sets. CDC 2015: 6603-6608 - [c60]Markus J. Kögel, Rolf Findeisen:
Self-triggered, prediction-based control of Lipschitz nonlinear systems. ECC 2015: 2150-2155 - [i3]Timm Faulwasser, Rolf Findeisen:
Nonlinear Model Predictive Control for Constrained Output Path Following. CoRR abs/1502.02468 (2015) - [i2]Timm Faulwasser, Tobias Weber, Juan Pablo Zometa, Rolf Findeisen:
Implementation of Nonlinear Model Predictive Path-Following Control for an Industrial Robot. CoRR abs/1506.09084 (2015) - 2014
- [j19]Matthias Rausch, Reinhardt Klein, Stefan Streif, Christian Pankiewitz, Rolf Findeisen:
Modellbasierte Zustandsschätzung für Lithium-Ionen-Batterien. Autom. 62(4): 296-311 (2014) - [j18]Timm Faulwasser, Veit Hagenmeyer, Rolf Findeisen:
Constrained reachability and trajectory generation for flat systems. Autom. 50(4): 1151-1159 (2014) - [j17]Joseph K. Scott, Rolf Findeisen, Richard D. Braatz, Davide Martino Raimondo:
Input design for guaranteed fault diagnosis using zonotopes. Autom. 50(6): 1580-1589 (2014) - [j16]Masako Kishida, Philipp Rumschinski, Rolf Findeisen, Richard D. Braatz:
Efficient Polynomial-Time Outer Bounds on State Trajectories for Uncertain Polynomial Systems Using Skewed Structured Singular Values. IEEE Trans. Autom. Control. 59(11): 3063-3068 (2014) - [c59]Matthias Rausch, Reinhardt Klein, Stefan Streif, Christian Pankiewitz, Rolf Findeisen:
Set-based state of charge estimation for lithium-ion batteries. ACC 2014: 1566-1571 - [c58]Ali Mesbah, Stefan Streif, Rolf Findeisen, Richard D. Braatz:
Stochastic nonlinear model predictive control with probabilistic constraints. ACC 2014: 2413-2419 - [c57]Markus J. Kögel, Rolf Findeisen:
On self-triggered reduced-attention control for constrained systems. CDC 2014: 2795-2801 - [c56]Joel A. Paulson, Ali Mesbah, Stefan Streif, Rolf Findeisen, Richard D. Braatz:
Fast stochastic model predictive control of high-dimensional systems. CDC 2014: 2802-2809 - [c55]Markus J. Kögel, Rolf Findeisen:
Stabilization of inexact MPC schemes. CDC 2014: 5922-5928 - [c54]Markus J. Kögel, Rolf Findeisen:
On MPC based trajectory tracking. ECC 2014: 121-127 - [c53]Joel A. Paulson, Davide Martino Raimondo, Rolf Findeisen, Richard D. Braatz, Stefan Streif:
Guaranteed active fault diagnosis for uncertain nonlinear systems. ECC 2014: 926-931 - [e1]Peter Benner, Rolf Findeisen, Dietrich Flockerzi, Udo Reichl, Kai Sundmacher:
Large-Scale Networks in Engineering and Life Sciences. Modeling and Simulation in Science, Engineering and Technology, Springer 2014, ISBN 978-3-319-08436-7 [contents] - 2013
- [j15]Reinhardt Klein, Nalin A. Chaturvedi, Jake Christensen, Jasim Ahmed, Rolf Findeisen, Aleksandar Kojic:
Electrochemical Model Based Observer Design for a Lithium-Ion Battery. IEEE Trans. Control. Syst. Technol. 21(2): 289-301 (2013) - [c52]Timm Faulwasser, Janine Matschek, Pablo Zometa, Rolf Findeisen:
Predictive path-following control: Concept and implementation for an industrial robot. CCA 2013: 128-133 - [c51]Vinzenz Bargsten, Pablo Zometa, Rolf Findeisen:
Modeling, parameter identification and model-based control of a lightweight robotic manipulator. CCA 2013: 134-139 - [c50]Matthias Rausch, Stefan Streif, Christian Pankiewitz, Rolf Findeisen:
Nonlinear observability and identifiability of single cells in battery packs. CCA 2013: 401-406 - [c49]Joseph K. Scott, Rolf Findeisen, Richard D. Braatz, Davide Martino Raimondo:
Design of active inputs for set-based fault diagnosis. ACC 2013: 3561-3566 - [c48]Pablo Zometa, Markus J. Kögel, Rolf Findeisen:
μAO-MPC: A free code generation tool for embedded real-time linear model predictive control. ACC 2013: 5320-5325 - [c47]Benjamin Kern, Rolf Findeisen:
Analysis and constrained control of nonlinear interconnected systems exploiting positively invariant family of sets. CDC 2013: 3806-3811 - [c46]Daniel Hast, Stefan Streif, Rolf Findeisen:
Guaranteed diagnosability of parametric faults in nonlinear systems. CDC 2013: 5662-5667 - [c45]Stefan Streif, Philipp Rumschinski, Didier Henrion, Rolf Findeisen:
Estimation of consistent parameter sets for continuous-time nonlinear systems using occupation measures and LMI relaxations. CDC 2013: 6379-6384 - [c44]Markus J. Kögel, Rolf Findeisen:
On efficient predictive control of linear systems subject to quadratic constraints using condensed, structure-exploiting interior point methods. ECC 2013: 27-34 - [c43]Stefan Streif, Matthias Karl, Rolf Findeisen:
Outlier analysis in set-based estimation for nonlinear systems using convex relaxations. ECC 2013: 2921-2926 - [c42]Steffen Borchers, Rolf Findeisen:
Outlier Detection for Polynomial Systems Using Semidefinite Relaxations. NOLCOS 2013: 761-766 - [c41]Markus J. Kögel, Rolf Findeisen:
Stability of NMPC with Cyclic Horizons. NOLCOS 2013: 809-814 - 2012
- [j14]Sasa V. Rakovic, Basil Kouvaritakis, Rolf Findeisen, Mark Cannon:
Homothetic tube model predictive control. Autom. 48(8): 1631-1638 (2012) - [j13]Stefan Streif, Anton Savchenko, Philipp Rumschinski, Steffen Borchers, Rolf Findeisen:
ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative-quantitative modeling. Bioinform. 28(9): 1290-1291 (2012) - [j12]Markus Krauss, Stephan Schaller, Steffen Borchers, Rolf Findeisen, Jörg Lippert, Lars Kuepfer:
Integrating Cellular Metabolism into a Multiscale Whole-Body Model. PLoS Comput. Biol. 8(10) (2012) - [j11]Sasa V. Rakovic, Basil Kouvaritakis, Mark Cannon, Christos Panos, Rolf Findeisen:
Parameterized Tube Model Predictive Control. IEEE Trans. Autom. Control. 57(11): 2746-2761 (2012) - [c40]Pablo Zometa, Markus J. Kögel, Timm Faulwasser, Rolf Findeisen:
Implementation aspects of model predictive control for embedded systems. ACC 2012: 1205-1210 - [c39]Philipp Rumschinski, Dina Shona Laila, Rolf Findeisen:
Discrete-to-continuous dynamics reconstruction for bilinear systems. CDC 2012: 172-177 - 2011
- [j10]Monica Schliemann, Eric Bullinger, Steffen Borchers, Frank Allgöwer, Rolf Findeisen, Peter Scheurich:
Heterogeneity reduces sensitivity of cell death for TNF-Stimuli. BMC Syst. Biol. 5: 204 (2011) - [j9]Steffen Borchers, Sandro Bosio, Rolf Findeisen, Utz-Uwe Haus, Philipp Rumschinski, Robert Weismantel:
Graph problems arising from parameter identification of discrete dynamical systems. Math. Methods Oper. Res. 73(3): 381-400 (2011) - [c38]Markus J. Kögel, Rolf Findeisen:
Fast predictive control of linear, time-invariant systems using an algorithm based on the fast gradient method and augmented Lagrange multipliers. CCA 2011: 780-785 - [c37]Reinhardt Klein, Nalin A. Chaturvedi, Jake Christensen, Jasim Ahmed, Rolf Findeisen, Aleksandar Kojic:
Optimal charging strategies in lithium-ion battery. ACC 2011: 382-387 - [c36]Paolo Varutti, Rolf Findeisen:
Event-based NMPC for networked control systems over UDP-like communication channels. ACC 2011: 3166-3171 - [c35]Markus J. Kögel, Rolf Findeisen:
Robust suboptimal control over lossy networks using extended input schemes. CACSD 2011: 210-215 - [c34]Masako Kishida, Philipp Rumschinski, Rolf Findeisen, Richard D. Braatz:
Efficient polynomial-time outer bounds on state trajectories for uncertain polynomial systems using skewed structured singular values. CACSD 2011: 216-221 - [c33]Markus J. Kögel, Rolf Findeisen:
Fast predictive control of linear systems combining Nesterov's gradient method and the method of multipliers. CDC/ECC 2011: 501-506 - [c32]Steffen Borchers, Rolf Findeisen:
Design of experiments for guaranteed parameter estimation in membership setting. CDC/ECC 2011: 2602-2607 - [c31]Timm Faulwasser, Rolf Findeisen:
A model predictive control approach to trajectory tracking problems via time-varying level sets of Lyapunov functions. CDC/ECC 2011: 3381-3386 - [i1]Rolf Findeisen, Lars Grüne, Jürgen Pannek, Paolo Varutti:
Robustness of Prediction Based Delay Compensation for Nonlinear Systems. CoRR abs/1105.3268 (2011) - 2010
- [j8]Philipp Rumschinski, Steffen Borchers, Sandro Bosio, Robert Weismantel, Rolf Findeisen:
Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks. BMC Syst. Biol. 4: 69 (2010) - [c30]Solvey Maldonado, Anton Savchenko, Rolf Findeisen:
Therapy Discrimination via Global Sensitivity Analysis of Force-induced Bone Growth and Adaptation. CCA 2010: 499-505 - [c29]Reinhardt Klein, Nalin A. Chaturvedi, Jake Christensen, Jasim Ahmed, Rolf Findeisen, Aleksandar Kojic:
State estimation of a reduced electrochemical model of a lithium-ion battery. ACC 2010: 6618-6623 - [c28]Paolo Varutti, Timm Faulwasser, Benjamin Kern, Markus J. Kögel, Rolf Findeisen:
Event-based reduced-attention predictive control for nonlinear uncertain systems. CACSD 2010: 1085-1090 - [c27]Philipp Rumschinski, Dina Shona Laila, Steffen Borchers, Rolf Findeisen:
Influence of discretization errors on set-based parameter estimation. CDC 2010: 296-301 - [c26]Sasa V. Rakovic, Benjamin Kern, Rolf Findeisen:
Practical set invariance for decentralized discrete time systems. CDC 2010: 3283-3288
2000 – 2009
- 2009
- [j7]Timm Faulwasser, Benjamin Kern, Paolo Varutti, Rolf Findeisen:
Prädiktive Regelung nichtlinearer Systeme unter asynchronen Mess- und Stellsignalen (Nonlinear Predictive Control based on Asynchronous Measurement and Control Signals). Autom. 57(6): 279-286 (2009) - [j6]Timm Faulwasser, Rolf Findeisen:
Ein prädiktiver Ansatz zur Lösung nichtlinearer Pfadverfolgungsprobleme unter Beschränkungen (A Predictive Solution to Nonlinear Path-Following Problems Subject to Constraints). Autom. 57(8): 386-394 (2009) - [j5]David Q. Mayne, Sasa V. Rakovic, Rolf Findeisen, Frank Allgöwer:
Robust output feedback model predictive control of constrained linear systems: Time varying case. Autom. 45(9): 2082-2087 (2009) - [c25]Paolo Varutti, Rolf Findeisen:
On the synchronization problem for the stabilization of networked control systems over nondeterministic networks. ACC 2009: 2216-2221 - [c24]Paolo Varutti, Benjamin Kern, Timm Faulwasser, Rolf Findeisen:
Event-based model predictive control for Networked Control Systems. CDC 2009: 567-572 - [c23]Steffen Borchers, Philipp Rumschinski, Sandro Bosio, Robert Weismantel, Rolf Findeisen:
A set-based framework for coherent model invalidation and parameter estimation of discrete time nonlinear systems. CDC 2009: 6786-6792 - [c22]Timm Faulwasser, Benjamin Kern, Rolf Findeisen:
Model predictive path-following for constrained nonlinear systems. CDC 2009: 8642-8647 - [c21]Paolo Varutti, Rolf Findeisen:
Compensating network delays and information loss by predictive control methods. ECC 2009: 1722-1727 - [c20]Christoph Böhm, Shuyou Yu, Rolf Findeisen, Frank Allgöwer:
Predictive control for lure systems subject to constraints using LMIs. ECC 2009: 3389-3394 - 2008
- [j4]Eric Bullinger, Dirk Fey, Marcello Farina, Rolf Findeisen:
Identifikation biochemischer Reaktionsnetzwerke: Ein beobachterbasierter Ansatz (Identification of Biochemical Reaction Networks: An Observer based Approach). Autom. 56(5): 269-280 (2008) - [c19]Christoph Böhm, Tobias Raff, Rolf Findeisen, Frank Allgöwer:
Calculating the terminal region of NMPC for Lure systems via LMIs. ACC 2008: 1127-1132 - [c18]Dara Geffen, Rolf Findeisen, Monica Schliemann, Frank Allgöwer, Martin Guay:
Observability Based Parameter Identifiability for Biochemical Reaction Networks. ACC 2008: 2130-2135 - 2007
- [j3]Renato Lepore, Alain Vande Wouwer, Marcel Remy, Rolf Findeisen, Zoltán K. Nagy, Frank Allgöwer:
Optimization strategies for a MMA polymerization reactor. Comput. Chem. Eng. 31(4): 281-291 (2007) - 2006
- [j2]David Q. Mayne, Sasa V. Rakovic, Rolf Findeisen, Frank Allgöwer:
Robust output feedback model predictive control of constrained linear systems. Autom. 42(7): 1217-1222 (2006) - [c17]Marcello Farina, Rolf Findeisen, Eric Bullinger, Sergio Bittanti, Frank Allgöwer, Peter Wellstead:
Results Towards Identifiability Properties of Biochemical Reaction Networks. CDC 2006: 2104-2109 - [c16]David Q. Mayne, Sasa V. Rakovic, Rolf Findeisen, Frank Allgöwer:
Robust Output Feedback Model Predictive Control for Constrained Linear Systems under Uncertainty Based on Feed Forward and Positive Invariant Feedback Control. CDC 2006: 6618-6623 - [c15]Solvey Maldonado, Steffen Borchers, Rolf Findeisen, Frank Allgöwer:
Mathematical Modeling and Analysis of Force Induced Bone Growth. EMBC 2006: 3154-3157 - 2005
- [c14]Rolf Findeisen, Frank Allgöwer:
Robustness Properties and Output Feedback of Optimization Based Sampled-data Open-loop Feedback. CDC/ECC 2005: 54-59 - [c13]Ignacio Alvarado, Rolf Findeisen, Peter Kuhl, Frank Allgöwer, Daniel Limón:
State Estimation for Repetitive Processes Using Iteratively Improving Moving Horizon Observers. CDC/ECC 2005: 7756-7761 - 2004
- [c12]Andrey Yonchev, Rolf Findeisen, Christian Ebenbauer, Frank Allgöwer:
Model predictive control of linear continuous time singular systems subject to input constraints. CDC 2004: 2047-2052 - 2003
- [j1]Rolf Findeisen, Lars Imsland, Frank Allgöwer:
State and Output Feedback Nonlinear Model Predictive Control: An Overview. Eur. J. Control 9(2-3): 190-206 (2003) - [c11]Lars Imsland, Rolf Findeisen, Frank Allgöwer, Bjarne A. Foss:
Output feedback stabilization with nonlinear predictive control: asymptotic properties. ACC 2003: 4908-4913 - [c10]Moritz Diehl, Rolf Findeisen, Frank Allgöwer, Hans Georg Bock, Johannes P. Schlöder:
Stability of nonlinear model predictive control in the presence of errors due to numerical online optimization. CDC 2003: 1419-1424 - [c9]Rolf Findeisen, Lars Imsland, Frank Allgöwer, Bjame A. Foss:
Stability conditions for observer based output feedback stabilization with nonlinear model predictive control. CDC 2003: 1425-1430 - [c8]Patrick Menold, Rolf Findeisen, Frank Allgöwer:
Finite time convergent observers for nonlinear systems. CDC 2003: 5673-5678 - [c7]Rolf Findeisen, Lars Imsland, Frank Allgöwer, Bjarne A. Foss:
Output-feedback nonlinear model predictive control using high-gain observers in original coordinates. ECC 2003: 2014-2019 - 2002
- [c6]Rolf Findeisen, Moritz Diehl, Tobias Bürner, Frank Allgöwer, Hans Georg Bock, Johannes P. Schlöder:
Efficient output feedback nonlinear model predictive control. ACC 2002: 4752-4757 - [c5]Rolf Findeisen, Moritz Diehl, Ilknur Disli-Uslu, Stefan Schwarzkopf, Frank Allgöwer, Hans Georg Bock, Johannes P. Schlöder, Ernst Dieter Gilles:
Computation and performance assessment of nonlinear model predictive control. CDC 2002: 4613-4618 - 2001
- [c4]Rolf Findeisen, Moritz Diehl, Zoltán K. Nagy, Frank Allgöwer, Hans Georg Bock, Johannes P. Schlöder:
Computational feasibility and performance of nonlinear model predictive control schemes. ECC 2001: 957-961 - 2000
- [c3]Rolf Findeisen, Hong Chen, Frank Allgöwer:
Nonlinear predictive control for setpoint families. ACC 2000: 260-264 - [c2]Eric Bullinger, Rolf Findeisen, Frantisek Kraus, Frank Allgöwer:
Some further results on adaptive λ-tracking for linear systems with high relative degree. ACC 2000: 3655-3660 - [c1]Zoltán K. Nagy, Rolf Findeisen, Moritz Diehl, Frank Allgöwer, Hans Georg Bock, Paul Serban Agachi, Johannes P. Schlöder, Daniel B. Leineweber:
Real-time feasibility of nonlinear predictive control for large scale processes-a case study. ACC 2000: 4249-4253
Coauthor Index
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