1 citations · 1 across the 3 of their papers we have counts for
3 papers
Rollout Then Optimize: A One-Step Newton Refinement of Learned Policies for Nonlinear Model Predictive Control
Andrea Ghezzi, Rudolf Reiter, Katrin Baumgärtner +2
We propose a computationally efficient rollout-then-optimize method to improve a learned control policy at deployment time. A learned policy provides a nominal trajectory, which is…
Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification
Rudolf Reiter, Jasper Hoffmann, Dirk Reinhardt +6
The fields of MPC and RL consider two successful control techniques for Markov decision processes. Both approaches are derived from similar fundamental principles, and both are wid…
Multi-Phase Optimal Control Problems for Efficient Nonlinear Model Predictive Control with acados
Jonathan Frey, Katrin Baumgärtner, Gianluca Frison +1
Computationally efficient nonlinear model predictive control relies on elaborate discrete-time optimal control problem (OCP) formulations trading off accuracy with respect to the c…