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Design of Identification and Compensation Methods for Space Rider GNC Algorithms

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The ESA Space Rider System is designed to provide Europe with the first reusable and independent end-to-end orbital platform, to deliver an uncrewed orbital laboratory able to de-orbit, re-enter, land and be relaunched after limited refurbishment. In this context, AVIO is the prime contractor of the support module that must guarantee the guidance, navigation and control functions during the orbital phase of the system. High versatility and reliability are thus requested for the AVUM Orbital Module since the Space Rider mission foresees various in-orbit experiments, ranging from payload for commercial and institutional applications to In Orbit Verification/Demonstration missions, microgravity experiments, and Earth/Space observation. From this perspective, it becomes of paramount importance to manage all the operative conditions for which the GNC must guarantee the best performance in terms of accuracy and operative duration. Attitude sensors must guarantee high data reliability despite being subjected to stresses during launch, a harsh operating environment and not least any assembly errors during integration. Constant in-orbit calibration is, therefore, necessary to meet requirements. Actuators, on the other hand, must be able to compensate for system and external uncertainties and manage any non-nominal condition. In particular, the malfunctioning or degraded behaviours of actuators are to be taken into account. The objective of this thesis is to investigate the counteract action that the Space Rider’s GNC must implement to identify and compensate for all the effects that could degrade the mission performance. Specifically, both sensor and actuator issues are addressed. To achieve this, sliding mode techniques are used for both identification and compensation phases, combined with closed-loop analysis of sensors and actuators. The performance and robustness of these algorithms are then demonstrated using simulations of real operating conditions that Space Rider will face in future missions.
Title: Design of Identification and Compensation Methods for Space Rider GNC Algorithms
Description:
The ESA Space Rider System is designed to provide Europe with the first reusable and independent end-to-end orbital platform, to deliver an uncrewed orbital laboratory able to de-orbit, re-enter, land and be relaunched after limited refurbishment.
In this context, AVIO is the prime contractor of the support module that must guarantee the guidance, navigation and control functions during the orbital phase of the system.
High versatility and reliability are thus requested for the AVUM Orbital Module since the Space Rider mission foresees various in-orbit experiments, ranging from payload for commercial and institutional applications to In Orbit Verification/Demonstration missions, microgravity experiments, and Earth/Space observation.
From this perspective, it becomes of paramount importance to manage all the operative conditions for which the GNC must guarantee the best performance in terms of accuracy and operative duration.
Attitude sensors must guarantee high data reliability despite being subjected to stresses during launch, a harsh operating environment and not least any assembly errors during integration.
Constant in-orbit calibration is, therefore, necessary to meet requirements.
Actuators, on the other hand, must be able to compensate for system and external uncertainties and manage any non-nominal condition.
In particular, the malfunctioning or degraded behaviours of actuators are to be taken into account.
The objective of this thesis is to investigate the counteract action that the Space Rider’s GNC must implement to identify and compensate for all the effects that could degrade the mission performance.
Specifically, both sensor and actuator issues are addressed.
To achieve this, sliding mode techniques are used for both identification and compensation phases, combined with closed-loop analysis of sensors and actuators.
The performance and robustness of these algorithms are then demonstrated using simulations of real operating conditions that Space Rider will face in future missions.

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