no code implementations • 7 Aug 2023 • Gianni Bianchini, Andrea Garulli, Antonio Giannitrapani, Mirko Leomanni, Renato Quartullo
This paper presents a machine learning approach for tuning the parameters of a family of stabilizing controllers for orbital tracking.
no code implementations • 15 Jul 2021 • Mirko Leomanni, Renato Quartullo, Gianni Bianchini, Andrea Garulli, Antonio Giannitrapani
In this paper, the trajectory planning problem for autonomous rendezvous and docking between a controlled spacecraft and a tumbling target is addressed.
no code implementations • 13 Nov 2019 • Francesco Farina, Stefano Melacci, Andrea Garulli, Antonio Giannitrapani
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.
1 code implementation • 17 Mar 2018 • Francesco Farina, Andrea Garulli, Antonio Giannitrapani, Giuseppe Notarstefano
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