Minimum-fuel Spacecraft Rendezvous based on Sparsity Promoting Optimization

TL;DR

This paper introduces a novel approach for spacecraft rendezvous that minimizes fuel use by applying sparsity-promoting optimization techniques, specifically IRLS, to compute efficient control sequences.

Contribution

It adapts compressive sensing algorithms to spacecraft control problems, providing a computationally efficient method for fuel minimization in rendezvous maneuvers.

Findings

Effective reduction in fuel consumption demonstrated through simulations

Sparsity-promoting optimization outperforms traditional methods

Applicable to both thrust vectoring and orthogonal vectoring scenarios

Abstract

In this paper, we consider the classical spacecraft rendezvous problem in which the so-called active spacecraft has to approach the target spacecraft which is moving in an elliptical orbit around a planet by using the minimum possible amount of fuel. Instead of using standard convex optimization tools which can be computationally expensive, we use modified versions of the Iteratively Reweighted Least Squares (IRLS) algorithm from compressive sensing to compute sparse optimal control sequences which minimize the fuel consumption for both thrust vectoring and orthogonal vectoring (active) spacecraft. Numerical simulations are performed to verify the efficacy of our approach.