Areostationary Satellite Station Keeping Via a Natural Motion Trajectory and Predictive Control

TL;DR

This paper introduces a novel predictive control method for Mars orbit satellites that leverages natural motion trajectories to reduce fuel consumption and computational complexity in station keeping.

Contribution

It proposes a new approach using natural motion trajectories and linearized MPC for efficient, fuel-saving station keeping of areostationary satellites around Mars.

Findings

Natural motion trajectories exist as limit cycles around Mars' stable points.

The MPC policy effectively minimizes fuel use while maintaining orbit constraints.

The method is computationally efficient for onboard implementation.

Abstract

Areostationary Mars orbit (AMO) satellites will play an important role in future expeditions to the Martian surface due to their strength as navigation and communication satellites. Perturbative forces experienced by an AMOR satellite will cause it to drift from its nominal orbit, necessitating station keeping. This note presents a novel approach to AMO station keeping that bridges the gap seen in prior predictive control methods between fuel-efficiency and computational-efficiency. The method proposed in this notes involves the discovery and use of a fuel-free natural motion trajectory that maintains the satellite within one degree of longitude from a areostationary orbit. Two of these natural motion trajectories exist as limit cycles about Mars' stable equilibrium longitudes. They are the resulting motion in the presence of Mars' non-homogeneous gravitational field, accounting for Keplerian and higher-order gravitational perturbations. The proposed MPC policy uses a linear time-varying (LTV) dynamic model that is derived by linearizing the satellite's dynamics relative to the appropriate natural motion trajectory. The result is a station keeping policy that minimizes the fuel consumed, maintains thrust and station-keeping constraints, and is computationally tractable for on-board implementation as a quadratic program.