CNCS Center for Nonlinear and Complex Systems
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Publications [#346738] of Silvia Ferrari

Papers Published

  1. Doerr, B; Linares, R; Zhu, P; Ferrari, S, Random finite set theory and optimal control of large spacecraft swarms, Advances in the Astronautical Sciences, vol. 168 (January, 2019), pp. 3729-3748, ISBN 9780877036593
    (last updated on 2021/09/05)

    Abstract:
    Controlling large swarms of robotic agents has many challenges including, but not limited to, computational complexity due to the number of agents, uncertainty in the functionality of each agent in the swarm, and uncertainty in the swarm’s configuration. This work generalizes the swarm state using Random Finite Set (RFS) theory and solves the control problem using Model Predictive Control (MPC) to overcome the aforementioned challenges. Computationally efficient solutions are obtained via the Iterative Linear Quadratic Regulator (ILQR). Information divergence is used to define the distance between the swarm RFS and the desired swarm configuration. Then, a stochastic optimal control problem is formulated using a modified L22 distance. Simulation results using MPC and ILQR show that swarm intensities converge to a target destination, and the RFS control formulation can vary in the number of target destinations. ILQR also provides a more computationally efficient solution to the RFS swarm problem when compared to the MPC solution. Lastly, the RFS control solution is applied to a spacecraft relative motion problem showing the viability for this real-world scenario.