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ORCIDKim Peter Wabersich
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2020 – today
- 2024
[c15]Nicolas Chatzikiriakos
, Kim Peter Wabersich, Felix Berkel, Patricia Pauli, Andrea Iannelli:
Learning soft constrained MPC value functions: Efficient MPC design and implementation providing stability and safety guarantees. L4DC 2024: 387-398- [i21]Nicolas Chatzikiriakos, Kim Peter Wabersich, Felix Berkel, Patricia Pauli, Andrea Iannelli:
Learning Soft Constrained MPC Value Functions: Efficient MPC Design and Implementation providing Stability and Safety Guarantees. CoRR abs/2401.07780 (2024) - [i20]Alexandre Didier, Andrea Zanelli, Kim Peter Wabersich, Melanie N. Zeilinger:
Predictive stability filters for nonlinear dynamical systems affected by disturbances. CoRR abs/2401.11183 (2024) - [i19]Elias Milios, Kim Peter Wabersich, Felix Berkel, Lukas Schwenkel:
Stability Mechanisms for Predictive Safety Filters. CoRR abs/2404.05496 (2024) - [i18]Amon Lahr, Joshua Näf, Kim Peter Wabersich, Jonathan Frey, Pascal Siehl, Andrea Carron, Moritz Diehl, Melanie N. Zeilinger:
L4acados: Learning-based models for acados, applied to Gaussian process-based predictive control. CoRR abs/2411.19258 (2024) - 2023
- [j9]Kim Peter Wabersich, Melanie N. Zeilinger:
Predictive Control Barrier Functions: Enhanced Safety Mechanisms for Learning-Based Control. IEEE Trans. Autom. Control. 68(5): 2638-2651 (2023) - [j8]Kim Peter Wabersich, Melanie N. Zeilinger:
Cautious Bayesian MPC: Regret Analysis and Bounds on the Number of Unsafe Learning Episodes. IEEE Trans. Autom. Control. 68(8): 4896-4903 (2023) - [c14]Alexandre Didier, Robin C. Jacobs, Jerome Sieber, Kim Peter Wabersich, Melanie N. Zeilinger:
Approximate Predictive Control Barrier Functions using Neural Networks: A Computationally Cheap and Permissive Safety Filter. ECC 2023: 1-7 - [c13]Simon Muntwiler, Kim Peter Wabersich, Robert Miklos, Melanie N. Zeilinger:
LQG for Constrained Linear Systems: Indirect Feedback Stochastic MPC with Kalman Filtering. ECC 2023: 1-7 - 2022
- [j7]Kim Peter Wabersich, Raamadaas Krishnadas, Melanie N. Zeilinger:
A Soft Constrained MPC Formulation Enabling Learning From Trajectories With Constraint Violations. IEEE Control. Syst. Lett. 6: 980-985 (2022) - [j6]Kim Peter Wabersich, Lukas Hewing, Andrea Carron, Melanie N. Zeilinger:
Probabilistic Model Predictive Safety Certification for Learning-Based Control. IEEE Trans. Autom. Control. 67(1): 176-188 (2022) - [c12]Ali Mesbah, Kim Peter Wabersich, Angela P. Schoellig, Melanie N. Zeilinger, Sergio Lucia, Thomas A. Badgwell, Joel A. Paulson:
Fusion of Machine Learning and MPC under Uncertainty: What Advances Are on the Horizon? ACC 2022: 342-357 - [c11]Johannes Köhler, Kim Peter Wabersich, Julian Berberich, Melanie N. Zeilinger:
State space models vs. multi-step predictors in predictive control: Are state space models complicating safe data-driven designs? CDC 2022: 491-498 - [c10]Simon Muntwiler, Kim Peter Wabersich, Melanie N. Zeilinger:
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers. L4DC 2022: 153-165 - [i17]Johannes Köhler, Kim Peter Wabersich, Julian Berberich, Melanie N. Zeilinger:
State space models vs. multi-step predictors in predictive control: Are state space models complicating safe data-driven designs? CoRR abs/2203.15471 (2022) - [i16]Alexandre Didier, Robin C. Jacobs, Jerome Sieber, Kim Peter Wabersich, Melanie N. Zeilinger:
Approximate Predictive Control Barrier Functions using Neural Networks: A Computationally Cheap and Permissive Safety Filter. CoRR abs/2211.15104 (2022) - [i15]Simon Muntwiler, Kim Peter Wabersich, Robert Miklos, Melanie N. Zeilinger:
LQG for Constrained Linear Systems: Indirect Feedback Stochastic MPC with Kalman Filtering. CoRR abs/2212.00351 (2022) - 2021
- [j5]Kim Peter Wabersich, Melanie N. Zeilinger:
A predictive safety filter for learning-based control of constrained nonlinear dynamical systems. Autom. 129: 109597 (2021) - [j4]Ben Tearle, Kim Peter Wabersich, Andrea Carron, Melanie N. Zeilinger:
A Predictive Safety Filter for Learning-Based Racing Control. IEEE Robotics Autom. Lett. 6(4): 7635-7642 (2021) - [j3]Andrea Carron, Kim Peter Wabersich, Melanie N. Zeilinger:
Plug-and-Play Distributed Safety Verification for Linear Control Systems With Bounded Uncertainties. IEEE Trans. Control. Netw. Syst. 8(3): 1501-1512 (2021) - [c9]Alexandre Didier, Kim Peter Wabersich, Melanie N. Zeilinger:
Adaptive Model Predictive Safety Certification for Learning-based Control. CDC 2021: 809-815 - [c8]Simon Muntwiler, Kim Peter Wabersich, Lukas Hewing, Melanie N. Zeilinger:
Data-Driven Distributed Stochastic Model Predictive Control with Closed-Loop Chance Constraint Satisfaction. ECC 2021: 210-215 - [i14]Ben Tearle, Kim Peter Wabersich, Andrea Carron, Melanie N. Zeilinger:
A predictive safety filter for learning-based racing control. CoRR abs/2102.11907 (2021) - [i13]Kim Peter Wabersich, Melanie N. Zeilinger:
Predictive control barrier functions: Enhanced safety mechanisms for learning-based control. CoRR abs/2105.10241 (2021) - [i12]Simon Muntwiler, Kim Peter Wabersich, Melanie N. Zeilinger:
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers. CoRR abs/2109.03962 (2021) - [i11]Alexandre Didier, Kim Peter Wabersich, Melanie N. Zeilinger:
Adaptive Model Predictive Safety Certification for Learning-based Control - Extended Version. CoRR abs/2109.13033 (2021) - 2020
- [j2]Lukas Hewing, Kim Peter Wabersich, Marcel Menner, Melanie N. Zeilinger:
Learning-Based Model Predictive Control: Toward Safe Learning in Control. Annu. Rev. Control. Robotics Auton. Syst. 3: 269-296 (2020) - [j1]Lukas Hewing, Kim Peter Wabersich, Melanie N. Zeilinger:
Recursively feasible stochastic model predictive control using indirect feedback. Autom. 119: 109095 (2020) - [c7]Kim Peter Wabersich, Melanie N. Zeilinger:
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling. L4DC 2020: 455-464 - [i10]Simon Muntwiler, Kim Peter Wabersich, Lukas Hewing, Melanie N. Zeilinger:
Data-Driven Distributed Stochastic Model Predictive Control with Closed-Loop Chance Constraint Satisfaction. CoRR abs/2004.02907 (2020) - [i9]Kim Peter Wabersich, Melanie N. Zeilinger:
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling. CoRR abs/2005.11744 (2020) - [i8]Kim Peter Wabersich, Melanie N. Zeilinger:
Performance and safety of Bayesian model predictive control: Scalable model-based RL with guarantees. CoRR abs/2006.03483 (2020)
2010 – 2019
- 2019
- [i7]Kim Peter Wabersich, Lukas Hewing, Andrea Carron, Melanie N. Zeilinger:
Probabilistic model predictive safety certification for learning-based control. CoRR abs/1906.10417 (2019) - [i6]Simon Muntwiler, Kim Peter Wabersich, Andrea Carron, Melanie N. Zeilinger:
Distributed Model Predictive Safety Certification for Learning-based Control. CoRR abs/1911.01832 (2019) - 2018
- [c6]Kim Peter Wabersich, Melanie N. Zeilinger:
Linear Model Predictive Safety Certification for Learning-Based Control. CDC 2018: 7130-7135 - [c5]Kim Peter Wabersich, Florian A. Bayer, Matthias Albrecht Müller, Frank Allgöwer:
Economic Model Predictive Control for Robust Periodic Operation with Guaranteed Closed-Loop Performance. ECC 2018: 507-513 - [c4]Lukas Hewing, Andrea Carron, Kim Peter Wabersich, Melanie N. Zeilinger:
On a Correspondence between Probabilistic and Robust Invariant Sets for Linear Systems. ECC 2018: 1642-1647 - [c3]Kim Peter Wabersich, Melanie N. Zeilinger:
Scalable synthesis of safety certificates from data with application to learning-based control. ECC 2018: 1691-1697 - [i5]Kim Peter Wabersich, Melanie N. Zeilinger:
Linear model predictive safety certification for learning-based control. CoRR abs/1803.08552 (2018) - [i4]Kim Peter Wabersich, Melanie N. Zeilinger:
Safe exploration of nonlinear dynamical systems: A predictive safety filter for reinforcement learning. CoRR abs/1812.05506 (2018) - [i3]Lukas Hewing, Kim Peter Wabersich, Melanie N. Zeilinger:
Recursively Feasible Stochastic Model Predictive Control using Indirect Feedback. CoRR abs/1812.06860 (2018) - 2017
- [i2]Kim Peter Wabersich, Melanie N. Zeilinger:
Scalable synthesis of safety certificates from data with application to learning-based control. CoRR abs/1711.11417 (2017) - 2016
- [c2]Julian Schlechtriemen, Kim Peter Wabersich, Klaus-Dieter Kuhnert:
Wiggling through complex traffic: Planning trajectories constrained by predictions. Intelligent Vehicles Symposium 2016: 1293-1300 - [i1]Kim Peter Wabersich, Marc Toussaint:
Advancing Bayesian Optimization: The Mixed-Global-Local (MGL) Kernel and Length-Scale Cool Down. CoRR abs/1612.03117 (2016) - 2015
- [c1]Kim Peter Wabersich, Marc Toussaint:
Automatic testing and minimax optimization of system parameters for best worst-case performance. IROS 2015: 5533-5539
Coauthor Index
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