Research activities of the MicroSatellite and Satellite Systems Laboratory include: -Cold and hot gas micropropulsion systems -Autonomous GNSS navigation systems -Ground segment and mission control technologies -Attitude and orbit control systems for nanosatellites The laboratory is working in partnership with both space agencies and industrial companies
The focus is on the study and development of accurate and cost effective solutions for autonomous real time orbit determination on board of micro- and nano- satellite platforms. In order to meet the typical requirements of the small satellites in terms of reduced development costs and time, as well as volume and power available on board, these navigation subsystems exploits the GNSS signals using COTS receivers. This relatively simple hardware architecture is coupled with sophisticated navigation algorithms in order to achieve positioning accuracy on board of a microsatellite similar to the ones delivered by commercial space-borne receivers, but at a fraction of the cost.
A model of this navigation subsystem, designed for microsatellite platforms, was validated and launched into LEO orbit on 3 December 2018, in the framework of the ESA ESEO project.
Pointing accuracy and stability is critical in S/C operation. Algorithms for attitude control and determination of nanosatellites rely on limited hardware and have to meet specific requirements. As part of the laboratory work, advanced control topics are employed to guarantee a higher level of performance in nanosatellites operation.
The Attitude Determination and Control System (ADCS) is a crucial subsystem in a spacecraft and one the major source of mission failures. To guarantee reliability of related algorithms and hardware, they have to be tested on-ground. The on-orbit environment is simulated thanks to the simulation testbed developed inside the laboratory to test nanosatellites ADCS. As part of the laboratory work the developed algorithms are validated on the testbed
This co-sponsored research project (ESA Open Space Innovation Platform) aims to improve the autonomy of future spacecraft missions requiring highly agile attitude maneuvers using variable-speed control moment gyroscopes (VSCMGs). While reaction wheels are often preferred for their simplicity, VSCMGs offer significant advantages in terms of agility, energy efficiency, and singularity management. Recent advances in machine learning have shown that neural networks are a promosing alternative to traditional model predictive control. Even under challenging nonlinear conditions, they can approximate optimal state feedback policies at a significantly lower computational cost.
The developed guidance & control algorithms will be benchmarked against established Attitude and Orbit Control Systems in simulations and hardware-in-the-loop experiments at the Attitude Control Air Bearing Facility (ESA-ESTEC).