A Nonlinear Predictive Control Strategy for Landing on an Asteroid

Autonomous operation of spacecraft near small bodies requires advanced Guidance, Navigation, and Control (GNC) capabilities to ensure safety and to enable scientific and economic activity. This paper proposes a Nonlinear Model Predictive Control (NMPC) strategy in the context of an autonomous descent and landing mission to the surface of the asteroid Eros 433 as part of a complete GNC architecture. The GNC architecture integrates the NMPC based translational controller with an attitude control system, reference trajectory generator, feature point-based state estimator, and gravity disturbance compensator. Simulation results using only output feedback from a high-fidelity simulator of Eros 433 that includes a gravity model, nonadditive measurement noise, and impulsive thrust model demonstrates the effectiveness of the proposed strategy.