Guidance of Reusable Launchers: Improving Descent and Landing Performance

Abstract

The sizing and capability definitions of reusable launchers during high-speed recovery are very challenging problems. In this paper, a convex optimization guidance algorithm for this type of system is proposed, based on performance improvements arising from the study of the coupled flight mechanics, guidance, and control problem. To appreciate the obtained improvements, tradeoff analyses of powered descent and landing scenarios are presented first using traditional guidance techniques. Subsequently, these results are refined by using the proposed online successive convex optimization-based guidance strategy. The descending over extended envelopes using successive convexification-based optimization (DESCENDO) algorithm has been designed as a middle ground between efficiency and optimality. This approach contrasts with previous convexification algorithms that either aimed at increasing computational efficiency (by typically disregarding aerodynamic deceleration) or reaching trajectory design optimality (by using exhaustive convex approximations). More critically, the algorithm is not confined to the mild coverage conditions assumed by previous approaches and can successfully handle the incorporation of the operational dynamics of reusable launchers. Insights provided by DESCENDO operating in a closed-loop fashion over full recovery scenarios enable a computationally efficient mission performance assessment.