Suboptimal Nonlinear Model Predictive Control Strategies for Tracking Near Rectilinear Halo Orbits

TL;DR

This paper explores the application of nonlinear model predictive control with low-thrust actuators for stabilizing spacecraft on Near Rectilinear Halo Orbits, demonstrating effective orbit maintenance with manageable computational demands.

Contribution

It introduces a suboptimal NMPC approach tailored for NRHO station-keeping, balancing control performance and computational efficiency.

Findings

NMPC successfully stabilizes spacecraft on NRHOs.

Control constraints are effectively handled by the proposed method.

Computational burden is reduced using specialized optimization routines.

Abstract

Near Rectilinear Halo Orbits (NRHOs), a subclass of halo orbits around the L1 and L2 Lagrange points, are promising candidates for future lunar gateways in cis-lunar space and as staging orbits for lunar missions. Closed-loop control is beneficial to compensate orbital perturbations and potential instabilities while maintaining spacecraft on NRHOs and performing relative motion maneuvers. This paper investigates the use of nonlinear model predictive control (NMPC) coupled with low-thrust actuators for station-keeping on NRHOs. It is demonstrated through numerical simulations that NMPC is able to stabilize a spacecraft to a reference orbit and handle control constraints. Further, it is shown that the computational burden of NMPC can be managed using specialized optimization routines and suboptimal approaches without jeopardizing closed-loop performance.