Multiple spacecraft rendezvous maneuvers by differential drag and low thrust engines

Abstract

A novel two-phase hybrid controller is proposed to optimize propellant consumption during multiple spacecraft rendezvous maneuvers in Low Earth Orbit. This controller exploits generated differentials in aerodynamic drag on each involved chaser spacecraft to effect a propellant-free trajectory near to the target spacecraft during the first phase of the maneuver, and then uses a fuel optimal control strategy via continuous low-thrust engines to effect a precision dock during the second phase. In particular, by varying the imparted aerodynamic drag force on each of the chaser spacecraft, relative differential accelerations are generated between each chaser and the target spacecraft along two of the three translational degrees of freedom. In order to generate this required differential, each chaser spacecraft is assumed to include a system of rotating flat panels. Additionally, each chaser spacecraft is assumed to have continuous low-thrust capability along the three translational degrees of freedom and full-axis attitude control. Sample simulations are presented to support the validity and robustness of the proposed hybrid controller to variations in the atmospheric density along with different spacecraft masses and ballistic coefficients. Furthermore, the proposed hybrid controller is validated against a complete nonlinear orbital model to include relative navigation errors typical of carrier-phase differential GPS (CDGPS). Limitations of the proposed controller appear relative to the target spacecraft's orbit eccentricity and a general characterization of the atmospheric density. Bounds on these variables are included

Application of a Differential Drag Controller to a Full System Simulation

“…For non-equatorial orbits, residual out of plane separation between the target and chaser spacecraft is expected, and may be controlled with a low-thrust engine. In this case, a hybrid control scheme such as the one proposed by Bevilacqua, Hall and Romano [5] may be employed.…”

“…Bevilacqua and Romano incorporated a linearized J 2 perturbation model into the development of their controller based on a modified set of HCW equations [4]. Bevilacqua, Hall and Romano have also proposed a hybrid control scheme involving both differential drag and a low thrust engine [5]. The use of differential drag reduces fuel consumption while the implementation of a low thrust engine gives the system greater controllability, particularly in the cross track direction, which is not achievable through differential drag alone.…”

Explicit Model Predictive Control Approach for Low-Thrust Spacecraft Proximity Operations

“…To enable this comparison, the boundary value problem (10) is solved using the commercial package DIDO, which implements pseudospectral (PS) methods [14]. A value of α 1 and β 0 is set in the cost function (8), with the terminal time t f and terminal condition xt f fixed as in the previous simulations. A good approximation of the optimal trajectory is obtained using 30 nodes for the PS solution.…”

“…Of particular interest in this field is the optimization of low-thrust formation flying trajectories, motivated by the application of miniaturized or high-efficiency propulsion technologies [7][8][9][10]. When two or more spacecraft in a formation are required to operate in close proximity, these trajectories must be safe with respect to collisions and other possible anomalies [11].…”

Hybrid planning for LEO long-duration multi-spacecraft rendezvous mission

“…The Lambert rendezvous algorithm, which is usually used in the large-angle orbital transfer problem, is not suitable for our problem that it is based on the two-body dynamic model [8]. The C-W (Clohessey-Whiltshire) equation with J 2 perturbation does not satisfy our requirement either and it is not applicable to the large-angle rendezvous problem [16][17][18]. If we directly use the nonlinear dynamic model with J 2 perturbation [19], the calculation of maneuver impulses is difficult, and the low-level problem would be a complicated nonlinear programming problem that is not convenient to be called a number of times by the up-level problem.…”