6 papers
MPC for underactuated spacecraft control with a Lyapunov supervised physics-informed neural network correction layer
Amirhossein Ayanmanesh Motlaghmofrad, Carlo Cena, Mauro Martini +1
Underactuated spacecraft faces controllability limitations and heightened sensitivity to environmental disturbances, complicating attitude maneuvering and stabilization. Due to the…
Hybrid Model Predictive Control with Physics-Informed Neural Network for Satellite Attitude Control
Carlo Cena, Mauro Martini, Marcello Chiaberge
Reliable spacecraft attitude control depends on accurate prediction of attitude dynamics, particularly when model-based strategies such as Model Predictive Control (MPC) are employ…
Learning Robust Satellite Attitude Dynamics with Physics-Informed Normalising Flow
Carlo Cena, Mauro Martini, Marcello Chiaberge
Attitude control is a fundamental aspect of spacecraft operations. Model Predictive Control (MPC) has emerged as a powerful strategy for these tasks, relying on accurate models of…
Fault injection analysis of Real NVP normalising flow model for satellite anomaly detection
Gabriele Greco, Carlo Cena, Umberto Albertin +2
Satellites are used for a multitude of applications, including communications, Earth observation, and space science. Neural networks and deep learning-based approaches now represen…
A Self-Supervised Task for Fault Detection in Satellite Multivariate Time Series
Carlo Cena, Silvia Bucci, Alessandro Balossino +1
In the space sector, due to environmental conditions and restricted accessibility, robust fault detection methods are imperative for ensuring mission success and safeguarding valua…
Physics-Informed Real NVP for Satellite Power System Fault Detection
Carlo Cena, Umberto Albertin, Mauro Martini +2
The unique challenges posed by the space environment, characterized by extreme conditions and limited accessibility, raise the need for robust and reliable techniques to identify a…