Larsén, Alexander KorsfeldtChen, YutaoBruschetta, MattiaCarli, RuggeroCenedese, AngeloVaragnolo, DamianoFelicetti, Leonard2019-12-092019-12-092019-11-25Larsen AK, Chen Y, Bruschetta M, et al., (2019) A computationally efficient model predictive control scheme for space debris rendezvous. IFAC-PapersOnLine, Volume 52, Issue 12, December 2019, pp.103-1102405-8963https://doi.org/10.1016/j.ifacol.2019.11.077https://dspace.lib.cranfield.ac.uk/handle/1826/14809We propose a non-linear model predictive scheme for planning fuel efficient maneuvers of small spacecrafts that shall rendezvous space debris. The paper addresses the specific issues of potential limited on-board computational capabilities and low-thrust actuators in the chasing spacecraft, and solves them by using a novel MatLab-based toolbox for real-time non-linear model predictive control (MPC) called MATMPC. This tool computes the MPC rendezvous maneuvering solution in a numerically efficient way, and this allows to greatly extend the prediction horizon length. This implies that the overall MPC scheme can compute solutions that account for the long time-scales that usually characterize the low-thrust rendezvous maneuvers. The so-developed controller is then tested in a realistic scenario that includes all the near- Earth environmental disturbances. We thus show, through numerical simulations, that this MPC method can successfully be used to perform a fuel-efficient rendezvous maneuver with an uncontrolled object, plus evaluate performance indexes such as mission duration, fuel consumption, and robustness against sensor and process noises.enAttribution-NonCommercial 4.0 InternationalNon Linear Model Predictive ControlNon-cooperative RendezvousSpace Debris RemovalLow-Thrust Manoeuvers,Constrained Optimization ProblemReal-time ControlArticle