An adaptive homotopy controller for low-thrust rendezvous uses MTF-augmented Kalman filter confidence to modulate control smoothness, reducing terminal miss distances by two orders of magnitude under degraded measurements.
Deep Networks as Approximators of Optimal Low -Thrust and Multi-Impulse Cost in Multitarget Missions
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 2roles
background 2polarities
background 2representative citing papers
Analytical gradients and Hessian for low-thrust rendezvous Δv enable efficient nonlinear programming of multi-asteroid trajectories.
citing papers explorer
-
Tightly-Coupled Estimation and Guidance for Robust Low-Thrust Rendezvous via Adaptive Homotopy
An adaptive homotopy controller for low-thrust rendezvous uses MTF-augmented Kalman filter confidence to modulate control smoothness, reducing terminal miss distances by two orders of magnitude under degraded measurements.
-
Nonlinear Programming of Low-Thrust Multi-Rendezvous Trajectories Using Analytical Hessian
Analytical gradients and Hessian for low-thrust rendezvous Δv enable efficient nonlinear programming of multi-asteroid trajectories.