Iterative-learning-control-based tracking for asteroid close-proximity operations

Iterative-learning-control (ILC)-based tracking for asteroid close-proximity operations is investigated in a study. To improve the orbiting and hovering tracking accuracy in the existence of the periodic perturbation, an ILC method is proposed, combined with a baseline feedback control. For such problems, the perturbation due to the irregular gravitational field is considered as the main source of the periodic perturbation. The feedback control is used to drive the spacecraft from the initial position to the desired orbit and maintain the trajectory under the nonperiodic perturbations. The benefits of the proposed ILC method on the scenarios of orbiting and inertial hovering around asteroid 243 Ida are demonstrated and analyzed with numerical simulations.