8 citations · 12 across the 5 of their papers we have counts for
3 papers · 1 filter
High-Dimensional Surrogate Modeling for Closed-Loop Learning of Neural-Network-Parameterized Model Predictive Control
Sebastian Hirt, Valentinus Suwanto, Hendrik Alsmeier +2
Learning controller parameters from closed-loop data has been shown to improve closed-loop performance. Bayesian optimization, a widely used black-box and sample-efficient learning…
Real-Time Non-Smooth MPC for Switching Systems: Application to a Three-Tank Process
Hendrik Alsmeier, Felix Häusser, Andreas Knödler +4
Real-time model predictive control of non-smooth switching systems remains challenging due to discontinuities and the presence of discrete modes, which complicate numerical integra…
Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification
Hendrik Alsmeier, Lukas Theiner, Anton Savchenko +2
This paper presents a framework for bounding the approximation error in imitation model predictive controllers utilizing neural networks. Leveraging the Lipschitz properties of the…