Kim Peter Wabersich

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 44

Top Topics

Constraint Violations

Predictive Control

Kalman Filtering

Top Venues

Publications

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)
Elias Milios, Kim Peter Wabersich, Felix Berkel, Lukas Schwenkel
Stability Mechanisms for Predictive Safety Filters. CoRR (2024)
Alexandre Didier, Andrea Zanelli, Kim Peter Wabersich, Melanie N. Zeilinger
Predictive stability filters for nonlinear dynamical systems affected by disturbances. CoRR (2024)
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 (2024)
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) (2023)
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)
Simon Muntwiler, Kim Peter Wabersich, Robert Miklos, Melanie N. Zeilinger
LQG for Constrained Linear Systems: Indirect Feedback Stochastic MPC with Kalman Filtering. ECC (2023)
Kim Peter Wabersich, Melanie N. Zeilinger
Predictive Control Barrier Functions: Enhanced Safety Mechanisms for Learning-Based Control. IEEE Trans. Autom. Control. 68 (5) (2023)
Simon Muntwiler, Kim Peter Wabersich, Melanie N. Zeilinger
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers. L4DC (2022)
Simon Muntwiler, Kim Peter Wabersich, Robert Miklos, Melanie N. Zeilinger
LQG for Constrained Linear Systems: Indirect Feedback Stochastic MPC with Kalman Filtering. CoRR (2022)
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 (2022)
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)
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 (2022)
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)
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) (2022)
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 (2022)
Kim Peter Wabersich, Melanie N. Zeilinger
Predictive control barrier functions: Enhanced safety mechanisms for learning-based control. CoRR (2021)
Alexandre Didier, Kim Peter Wabersich, Melanie N. Zeilinger
Adaptive Model Predictive Safety Certification for Learning-based Control - Extended Version. CoRR (2021)
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) (2021)
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)
Alexandre Didier, Kim Peter Wabersich, Melanie N. Zeilinger
Adaptive Model Predictive Safety Certification for Learning-based Control. CDC (2021)
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) (2021)
Simon Muntwiler, Kim Peter Wabersich, Melanie N. Zeilinger
Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers. CoRR (2021)
Kim Peter Wabersich, Melanie N. Zeilinger
A predictive safety filter for learning-based control of constrained nonlinear dynamical systems. Autom. 129 (2021)
Ben Tearle, Kim Peter Wabersich, Andrea Carron, Melanie N. Zeilinger
A predictive safety filter for learning-based racing control. CoRR (2021)
Lukas Hewing, Kim Peter Wabersich, Melanie N. Zeilinger
Recursively feasible stochastic model predictive control using indirect feedback. Autom. 119 (2020)
Kim Peter Wabersich, Melanie N. Zeilinger
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling. CoRR (2020)
Kim Peter Wabersich, Melanie N. Zeilinger
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling. L4DC (2020)
Kim Peter Wabersich, Melanie N. Zeilinger
Performance and safety of Bayesian model predictive control: Scalable model-based RL with guarantees. CoRR (2020)
Simon Muntwiler, Kim Peter Wabersich, Lukas Hewing, Melanie N. Zeilinger
Data-Driven Distributed Stochastic Model Predictive Control with Closed-Loop Chance Constraint Satisfaction. CoRR (2020)
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 (2020)
Kim Peter Wabersich, Lukas Hewing, Andrea Carron, Melanie N. Zeilinger
Probabilistic model predictive safety certification for learning-based control. CoRR (2019)
Simon Muntwiler, Kim Peter Wabersich, Andrea Carron, Melanie N. Zeilinger
Distributed Model Predictive Safety Certification for Learning-based Control. CoRR (2019)
Kim Peter Wabersich, Melanie N. Zeilinger
Linear Model Predictive Safety Certification for Learning-Based Control. CDC (2018)
Lukas Hewing, Andrea Carron, Kim Peter Wabersich, Melanie N. Zeilinger
On a Correspondence between Probabilistic and Robust Invariant Sets for Linear Systems. ECC (2018)
Kim Peter Wabersich, Melanie N. Zeilinger
Safe exploration of nonlinear dynamical systems: A predictive safety filter for reinforcement learning. CoRR (2018)
Lukas Hewing, Kim Peter Wabersich, Melanie N. Zeilinger
Recursively Feasible Stochastic Model Predictive Control using Indirect Feedback. CoRR (2018)
Kim Peter Wabersich, Melanie N. Zeilinger
Linear model predictive safety certification for learning-based control. CoRR (2018)
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)
Kim Peter Wabersich, Melanie N. Zeilinger
Scalable synthesis of safety certificates from data with application to learning-based control. ECC (2018)
Kim Peter Wabersich, Melanie N. Zeilinger
Scalable synthesis of safety certificates from data with application to learning-based control. CoRR (2017)
Kim Peter Wabersich, Marc Toussaint
Advancing Bayesian Optimization: The Mixed-Global-Local (MGL) Kernel and Length-Scale Cool Down. CoRR (2016)
Julian Schlechtriemen, Kim Peter Wabersich, Klaus-Dieter Kuhnert
Wiggling through complex traffic: Planning trajectories constrained by predictions. Intelligent Vehicles Symposium (2016)
Kim Peter Wabersich, Marc Toussaint
Automatic testing and minimax optimization of system parameters for best worst-case performance. IROS (2015)