Control methods for collision free low thrust deployment of large satellite constellations


The stage will be devoted to the analysis and design of the deployment of large satellite
constellations, sometimes called “mega constellations”, via low-thrust propulsion.
Although the minimization of classical figures of interest like energy consumption and
deployment time is desirable, the simultaneous maneuvering of several agents in a
possibly-clustered initial configuration is the key challenge of the problem. Hence, the
definition of a reliable and computationally-efficient control strategy that is capable of
preventing collisions between satellites of the constellation while achieving the
deployment is envisaged. However, owing to the large magnitude of orbital
perturbations to thrust ratio (i.e., the control authority is not sufficient to fully
compensate orbital drift) unavoidable collisions may occur for some initial configuration
of the constellation. Hence, special care will be devoted to control methods offering
guarantees on the safeness of the maneuver for some feasible set of initial conditions.

Objectives of the stage:

Control barrier functions enable the design of controllers capable of guaranteeing safe
maneuvers. The possibility of including constraints of high relative degree was recently
studied in the literature. These contributions are pertinent to tackle collision avoidance
of satellites because the constraint can be formulated as a function of the relative
position of the satellites, while controls are on their relative accelerations (hence, the
constraint is of relative degree 2). The stage is aimed at investigating the use of these
techniques in the framework of the deployment of a mega constellation. To this end, a
simplified problem will first be considered, namely a linear control system with bounds
on the maximum control action will be used to model the relative dynamics of only two
satellites. If time permits, the inclusion of more agents will be investigated. In view of a
perspective onboard implementation of the algorithms, special care will be devoted to
the computational efficiency of the controller.

Work environment:

For Master 1 or Master 2 students. The internship will take place in 2022 and it will last 4 to 6 months.

Advisors: Lamberto Dell’Elce, Jean-Baptiste Pomet

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