This paper describes the hardware-in-the-loop (HIL) simulation methodology used for the verification of functional requirements of e-st @r-I CubeSat. The satellite's behavior is investigated via HIL simulation, and the results obtained are consistent with the expected values in any operative conditions. It is proven that HIL simulation is a valuable means for supporting the verification process of small satellites and may help reduce the time and cost of the development phase and increase mission reliability.

The release and retrieval of a CubeSat from a big spacecraft is useful for the external inspection and monitoring of the big spacecraft. However, docking maneuvers during the retrieval are challenging since safety constraints and high performance must be achieved, considering the small dimensions and the actual small satellites technology. The trajectory control is crucial to have a soft, accurate, quick, and propellant saving docking. The present paper deals with the design of a tracking model predictive controller (TMPC) tuned to achieve the stringent docking requirements for the retrieval of a CubeSat within the cargo bay of a large cooperative vehicle. The performance of the TMPC is verified using a complex model that includes non-linearities, uncertainties of the CubeSat parameters, and environmental disturbances. Moreover, 300 Monte Carlo runs demonstrate the robustness of the TMPC solution.

Space Debris removal is a critical issue related to space research. One of the key requirements for a removal mission is the assessment of the target rotational dynamics. Ground observations are not sufficient for reaching the accuracy level required to guide the chaser spacecraft during the capture maneuver. Moreover, the guidance and control strategy for the chaser to approach the target is a critical aspect of such missions. This paper presents simulation results of two complementary methods, one for estimating the entire rotational dynamic state of the target and the other for accurately controlling the approach maneuver. In particular, the information coming from the identification and prediction of the actual motion of the tumbling axis of the target is exploited by the second method for aligning the docking interface of the chaser with that axis at the instant of capture. The dynamics estimation is based on Kalman filtering in an original combination with compressive sampling techniques for making the method robust to failures of observation sensors. The guidance of the chaser is based on a model predictive control law. The combined simulation of the employment of the methods has revealed the feasibility of the global approach.

Given the role of Cubesats in the new space economy, a statistically relevant number of CubeSats have flown, and considering the high percentage of failed missions, the investigation of in-orbit anomalies becomes of paramount importance. It is rare to find data about mission failures, probably because the partial or total absence of telemetry does not encourage any analysis. The lack of data from the spacecraft in orbit can be mitigated through ad-hoc verification campaigns on satellite models when in-orbit anomalies are experienced. This paper shows an effective testing activity conducted on models of the spacecraft to understand the root cause of a severe anomaly that occurred during mission operations. The tests are part of a comprehensive methodology for root causes analysis. The paper aims at sharing the experience built upon a practical case of interest. More importantly, this work has the ambition of fostering the research on key topics of reliability, mission operations and assembly, and integration and verification/test processes, which have shown to be critical. The activity presented in this paper demonstrates that investigating the anomalies can help recover the mission of interest but can also support building a heritage that is still missing for CubeSat missions today.