Adaptive Relative Orbit Control Considering Laser Ablation Uncertainty
arXiv:2608.16173
2026
Dynamics
1 ideas extracted · analyzed Sep 1, 2026
What the math gives to ML
The paper's transferable mechanism is adaptive cancellation of unknown dynamics: a Gaussian-process regression model estimates laser-ablation and atmospheric-drag disturbances, while feedback control stabilizes the known relative-orbit dynamics. The key asset is the separation between a structured nominal flow and a data-driven residual with an uncertainty estimate. A practical neural-network transfer is an uncertainty-gated residual compensator for optimizer dynamics, which learns repeatable minibatch and curvature-induced deviations from a nominal second-order update and applies compensation only when the GP is confident.
Ideas from this paper
Unverified
2026
Treat parameter optimization as a controlled dynamical system with a known nominal update and an unknown residual caused by minibatch noise, changing curvature, and optimizer-state mismatch. Fit a Gaussian process to the observed residual acceleration and subtract its posterior mean from the next update, with a confidence gate that suppresses compensation when posterior variance is large.
Useful6/10
Difficulty6/10
Novelty7/10