Artificial neural networks for control and propagation of low-thrust trajectories

The work is devoted to the design of artificial neural networks which can be used for the orbital control of a spacecraft equipped with a low-thrust engine. The problem of energy-optimal transfer between two points is considered. Two neural networks are constructed: the predictive one and the controlling one. Their architecture, learning algorithms, and the performance in the presence of unaccounted disturbances are given.