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20162026
most citedRobust adaptive MPC using control contraction metrics

61 citations · 221 across the 98 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

eess.SY2019★ 4 cited

Dual Stochastic MPC for Systems with Parametric and Structural Uncertainty

Elena Arcari, Lukas Hewing, Max Schlichting +1

Designing controllers for systems affected by model uncertainty can prove to be a challenge, especially when seeking the optimal compromise between the conflicting goals of identif…

cs.LG2019

On Simulation and Trajectory Prediction with Gaussian Process Dynamics

Lukas Hewing, Elena Arcari, Lukas P. Fröhlich +1

Established techniques for simulation and prediction with Gaussian process (GP) dynamics often implicitly make use of an independence assumption on successive function evaluations…

eess.SY2019

An Approximate Dynamic Programming Approach for Dual Stochastic Model Predictive Control

Elena Arcari, Lukas Hewing, Melanie N. Zeilinger

Dual control explicitly addresses the problem of trading off active exploration and exploitation in the optimal control of partially unknown systems. While the problem can be cast…

eess.SY2019

Distributed Model Predictive Safety Certification for Learning-based Control

Simon Muntwiler, Kim P. Wabersich, Andrea Carron +1

While distributed algorithms provide advantages for the control of complex large-scale systems by requiring a lower local computational load and less local memory, it is a challeng…

physics.med-ph2019

Knee Compliance Reduces Peak Swing Phase Collision Forces in a Lower-Limb Exoskeleton Leg: A Test Bench Evaluation

Stefan O. Schrade, Marcel Menner, Camila Shirota +5

Powered lower limb exoskeletons are a viable solution for people with a spinal cord injury to regain mobility for their daily activities. However, the commonly employed rigid actua…

eess.SY2019

Probabilistic model predictive safety certification for learning-based control

Kim P. Wabersich, Lukas Hewing, Andrea Carron +1

Reinforcement learning (RL) methods have demonstrated their efficiency in simulation environments. However, many applications for which RL offers great potential, such as autonomou…