5 papers
Scalable Nonlinear DeePC: Bridging Direct and Indirect Methods and Basis Reduction
Thomas O. de Jong, Mircea Lazar, Siep Weiland +1
This paper studies regularized data-enabled predictive control (DeePC) within a nonlinear framework and its relationship to subspace predictive control (SPC). The -regularizatio…
MPC for momentum counter-balanced and zero-impulse contact with a free-spinning satellite
Theofania Karampela, Rishie Seshadri, Florian Dörfler +1
In on-orbit robotics, a servicer satellite's ability to make contact with a free-spinning target satellite is essential to completing most on-orbit servicing (OOS) tasks. This manu…
Input-Output Data-Driven Representation: Non-Minimality and Stability
Joowon Lee, Nam Hoon Jo, Hyungbo Shim +2
Many recent data-driven control approaches for linear time-invariant systems are based on finite-horizon prediction of output trajectories using input-output data matrices. When ap…
SOMBRL: Scalable and Optimistic Model-Based RL
Bhavya Sukhija, Lenart Treven, Carmelo Sferrazza +3
We address the challenge of efficient exploration in model-based reinforcement learning (MBRL), where the system dynamics are unknown and the RL agent must learn directly from onli…
A Markov Decision Process Framework for Early Maneuver Decisions in Satellite Collision Avoidance
Francesca Ferrara, Lander W. Schillinger Arana, Florian Dörfler +1
We develop a Markov decision process (MDP) framework to autonomously make guidance decisions for satellite collision avoidance maneuver (CAM) and a reinforcement learning policy gr…