5 papers
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…
L4acados: Learning-based models for acados, applied to Gaussian process-based predictive control
Amon Lahr, Joshua Näf, Kim P. Wabersich +5
Incorporating learning-based models, such as artificial neural networks or Gaussian processes, into model predictive control (MPC) strategies can significantly improve control perf…
MPC4RL -- A Software Package for Reinforcement Learning based on Model Predictive Control
Dirk Reinhardt, Katrin Baumgärnter, Jonathan Frey +2
In this paper, we present an early software integrating Reinforcement Learning (RL) with Model Predictive Control (MPC). Our aim is to make recent theoretical contributions from th…
Towards Solutions of Manipulation Tasks via Optimal Control of Projected Dynamical Systems
Anton Pozharskiy, Armin NurkanoviÄ, Moritz Diehl
We introduce a modeling framework for manipulation planning based on the formulation of the dynamics as a projected dynamical system. This method uses implicit signed distance func…
First-Order Sweeping Processes and Extended Projected Dynamical Systems: Equivalence, Time-Discretization and Numerical Optimal Control
Anton Pozharskiy, Armin NurkanoviÄ, Moritz Diehl
Constrained dynamical systems are systems such that, by some means, the state stays within a given set. Two such systems are the (perturbed) Moreau sweeping process and the recentl…