Guidance of Reusable Launchers: Improving Descent and Landing Performance

Abstract

The sizing and capability definition of reusable launchers during high-speed recovery are very challenging problems. In this article, a convex optimisation guidance algorithm for this type of systems is proposed based on performance improvements arising from the study of the coupled flight mechanics, guidance and control problem. In order to appreciate the obtained improvements, trade-off 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 optimisation-based guidance strategy. The DESCENDO (Descending over Extended Envelopes using Successive Convexification-based Optimisation) 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.

Reusable Launchers: Development of a Coupled Flight Mechanics, Guidance, and Control Benchmark

“…This integrated G&C approach allowed to perform preliminary assessments of different RLV recovery strategies and of the controllability challenges encountered, while highlighting the existing room for improvement. For example, concerning guidance, more powerful approaches based on convex optimisation have shown promise (see [9,27]), while in terms of control, approaches based on robust algorithms as well as active load prediction and relief schemes are also expected to result in improved designs and mission gains.…”

“…lower and upper throttling magnitude and rate limits) and both of them are critical for RLV recovery. For this reason, more sophisticated algorithms such as those based on convex optimisation are being developed [9,27]. In the present article, aerodynamic and thermal load constraints are considered only through simulations.…”

“…These choices were made based on a detailed performance trade-off analysis between required propellant, dynamic pressure and touchdown velocity for different re-ignition altitudes, mission durations and single/double boost alternatives. This analysis is available in [9]. The top-left plot of Fig.…”

“…This very tight margin motivates the need for more performing recovery guidance algorithms. A follow-up investigation on improving the performance of the present baseline algorithm is provided in [9].…”

“…constant specific impulse throughout the flight) are tailored to the aforementioned aim of coupled flight mechanics and G&C studies, and configuration parameters (as well as G&C algorithms) can be easily modified and assessed thanks to its modular architecture. Indeed, this modularity has been used in reference [9] to develop and verify an on-board convex optimisation-based guidance algorithm termed DESCENDO (Descending over Extended Envelopes using Successive Convexification-based Optimisation).…”