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Found 6 papers, 1 papers with code
Adaptive Threshold Selection for Set Membership State Estimation with Quantized Measurements
Motivated by the possibility of suitably tuning the quantizer thresholds in sensor networks, the optimal design of adaptive quantizers is formulated in terms of the minimization of the radius of information associated to the state estimation problem.
Learning-based Parameter Optimization for a Class of Orbital Tracking Control Laws
This paper presents a machine learning approach for tuning the parameters of a family of stabilizing controllers for orbital tracking.
Variable-Horizon Guidance for Autonomous Rendezvous and Docking to a Tumbling Target
In this paper, the trajectory planning problem for autonomous rendezvous and docking between a controlled spacecraft and a tumbling target is addressed.
Optimal Low-Thrust Orbit Transfers Made Easy: A Direct Approach
The optimization of low-thrust, multi-revolution orbit transfer trajectories is often regarded as a difficult problem in modern astrodynamics.
Optimization and Control
Asynchronous Distributed Learning from Constraints
In this paper, the extension of the framework of Learning from Constraints (LfC) to a distributed setting where multiple parties, connected over the network, contribute to the learning process is studied.
Asynchronous Distributed Method of Multipliers for Constrained Nonconvex Optimization
We show that this distributed algorithm is equivalent to a block coordinate descent algorithm for the minimization of the Augmented Lagrangian followed by an update of the whole multiplier vector.
Optimization and Control
