This thesis aims to demonstrate the benefits that specific developments in the field of guidance and control can bring to space exploration. These benefits are mostly related to the improvement of planetary descent & landing techniques and reduction of launcher development and operation costs. The demonstration employs two application cases that are well-representative of the aforementioned benefits.
The first case study investigates the feasibility of applying robust control tools to design and optimise descent & landing trajectories. It is based on a sample return mission to the Martian moon Phobos, which is especially challenging because the irregular and poorly-known shape of this body renders its gravitational environment extremely uncertain and variable. By offering the ability to explicitly account for the effects of such an uncertain environment in a systematic manner, it is shown how robust control synthesis and analysis techniques can be effective in complementing and improving state-of-practice industrial approaches. Due to the conservative character of space industry, especial attention is given to techniques that allow to take advantage of legacy knowledge, such as structured H-infinity optimisation.
The second application is focused on sophisticated guidance and control architectures for reusable launch vehicles, which are seen as a key paradigm for sustainable access to space. Improving launcher performance is also a very demanding task since mission requirements tend to compete against each other due to fundamental couplings between trajectory, actuators and vehicle structure. A novel benchmark and design framework is first developed, featuring a real-time capable guidance algorithm for retro-propulsive descent and pinpoint landing, which relies on recent advances in the domain of convex optimisation. This reusable launcher benchmark is finally supplemented with dedicated solutions to analyse and minimise the impact of aerodynamic loads, which represent a critical driver of launcher safety and operational availability.
|Date of Award||28 Nov 2019|
- The University of Bristol
|Supervisor||Andres Marcos (Supervisor) & Mark H Lowenberg (Supervisor)|