04 Nov 2015
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Classroom 165, ground floor, Library, Aerospace Eng.
One of the key issues in future space technologies is the relative position control of a satellite cluster, known as cluster flight. Cluster flight entails maximal and minimal inter-satellite distance constraints, in order to prevent an unacceptable drift and avoid collisions.
The purpose of this research is to enable fuelless cluster flight by using differential-drag. This ability will render the thrusters unnecessary, which will constitute a breakthrough in the field of cluster flight. To that end, nonlinear differential drag-based controllers suitable for implementation in long-term missions were developed, for a cluster consisting of multiple modules. Numerical simulations show promising performance of the maximal distance controller. The minimal distance controller successfully prevents the cluster from colliding. These algorithms are planned to be implemented on-board the Space Autonomous Mission for Swarming and Geo-locating Nanosatellites (SAMSON).
Since any drag-based control algorithm must cope with significant uncertainties, the closed-loop system performance was examined through a covariance analysis. The method used for uncertainty quantification is the Linear Covariance Analysis.
Finally, a new analytical method for calculating the satellite projected cross-sectional areas and concomitant torques was developed. The knowledge of this area is essential for approximating the forces and torques induced by atmospheric drag and solar radiation pressure, and it is also required for implementing various attitude control modes.