Algorithmic Center of Rotation to Center of Mass Offset Estimation of a Spherical Air-breaing Attitude Simulator
- Paper ID
90375
- DOI
- author
- company
Zentrum für Telematik; S4 – Smart Small Satellite Systems GmbH; University Wuerzburg
- country
Germany
- year
2024
- abstract
A robust Attitude Determination and Control System (ADCS) is imperative for the success of nanosatellite missions with challenging engineering goals. ADCS performance parameters are tested on the ground using a fully integrated attitude test environment, including a space environment simulation and a near-friction-free three-axis rotary platform. In the context of ADCS verification, a three-axis rotary platform relies on a spherical air-bearing that accommodates the satellite's mechanical characteristics, such as the Centre of Mass (CoM), Center of Rotation (CoR) and the Moment of Inertia (MOI) tensor. However, setups with spherical air-bearings are susceptible to various disturbances, including gravitational torques, aerodynamic torques, and platform deformation/anisoelastic effects. These disturbances, when combined, can lead to ADCS actuator saturation, significantly impacting verification results. One significant source of disturbing torque is the gravitational torque arising from an offset between the CoM of the setup and the CoR of the platform. Even a small misalignment of 0.1mm between CoM and CoR for a 3U nanosatellite can result in a gravitational torque of up to 5 mN, significantly surpassing the reaction wheel torque used in 3U nanosatellite platforms. To effectively test ADCS in all three axes using the spherical air-bearing platform, mass balancing is conducted through the addition of small counterweights, aiming to nullify the gravitational torque. However, this process relies on CoM estimation provided by Computer-Aided Design (CAD) tools. While CAD tools are accurate in estimating mass properties, variations in actual material properties, such as density and homogeneity, and the inability to accurately model flexible structures can lead to significant differences. This paper explores the utilization of batch estimation, filtering, and adaptive control law-based algorithms for estimating the offset vector between the CoM and CoR. The offset estimation leverages onboard Inertial Measurement Unit (IMU) data or reference attitude data from an external tracking system. Evaluation of different algorithms is based on critical parameters, including accuracy, convergence rate, robustness, and ease of implementation. Zentrum für Telematik e. V. (ZfT) is currently engaged in the development of the Telematics Earth Observation Mission (TOM), which aims to demonstrate photogrammetric methods for monitoring Volcanic Ash clouds. The algorithms developed for CoM and CoR offset estimation will be employed in the ADCS test campaign for the TOM mission. This paper presents the results of offset estimation, comparing them against CAD data of the satellite, along with a quantitative analysis of performance parameters under various test conditions and discussions on corresponding calibration methods.