Guidance and Control Algorithms for Space Rendezvous and Docking Maneuvers

The Rendezvous and Docking (RVD) mission is one of the most complex and interesting space missions. Proximity operations and docking require extremely delicate and precise translational and rotational maneuvering. During the final approach of the proximity operations phase, the relative spacecraft states (position, velocity, attitude and angular rates) must be precisely controlled in order to obtain the required docking interface conditions. As a consequence, precise relative position, velocity and attitude state estimations are required. The on-board Guidance, Navigation, and Control (GNC) system can automatically perform various Rendezvous functions including translational and rotational control, targeting and relative navigation, but the final approach requires more attention and precision. Thus, the scope of this work is studying an automated RVD maneuver, implementing guidance and control algorithms to fulfill the RVD mission, without considering the docking of the two spacecraft. This paper describes definition and design of Guidance and Control (G&C) algorithms for space Rendezvous in order to take a moving vehicle, from some known or unknown state in terms of position and velocity, near or in contact with another one that is moving with defined parameters. The typical algorithms related to RVD are presented and the more promising are used for the simulator, combining them in unusual compounds. The paper is organized as follows. Section II describes the simulator mission profile and the mathematical model used in the simulator itself to reproduce the translation and rotation of the spacecraft. In Section III, the main architecture of the simulator is represented, in order to explain not only the Simulink model but also the functional concept itself. Whereas in Section IV, the attention is focused on the G&C algorithms implemented in this work. Finally, the results of several simulations are reported and compared between them in order to define the best G&C strategy between the proposed ones, that turns out to be the combination of a Proportional Navigation (PN) algorithm for the guidance and a Linear-Quadratic-Regulator (LQR) for the attitude control.