Input-Saturated Station Keeping for Celestial Body Orbits Using Iterative Learning Control

To balance the requirement of long lifespan and limited launch mass in celestial body orbiting missions, limited input is an inevitable factor for spacecraft controller design. To deal with disturbances and uncertainties and achieve high-precision station keeping around celestial body orbits, an input-saturated iterative learning control (ILC) method is presented in this article. Specifically, for station keeping, spacecraft is subject to periodic perturbation from the irregular gravitational field and aperiodic disturbances from third-body effects and solar radiation pressure. To this end, a scheme combining input-saturated ILC with feedback control is proposed to attenuate the periodic and aperiodic perturbations, respectively, improving the station-keeping tracking accuracy. Then, a composite energy function considering the alignment condition is proposed to prove the convergence of the presented method. Finally, the proposed ILC with input saturation is illustrated in detail through examples involving station keeping for mega-constellation and close proximity around the asteroid.