Design and Trajectory Optimisation for Space Access Aystems
System-level optimisation, both of the vehicle and its mission, is a key tool during the initial design phases of space access systems. This project encompasses a key application stream within the University of Strathclyde’s Aerospace Centre of Excellence developing computational tools to effectively optimise these complex systems. Integrating advanced computational intelligence methods, focusing on optimisation, optimal control, and surrogate modelling, with disciplinary models necessary for dynamics and control models, allows designers to evaluate operational
performance and cost on a system level and to better understand the trade-offs between the various subsystems.
This project combines many different work programmes, from PhD studentships to consultancies to public and industrially funded R&D work. In particular, this work includes a partnership with Orbital Access Limited to design and develop the Orbital-500R, a horizontal take-off and landing, two-stage space launch system for small payloads. This UK-based start-up is capitalising on the growing demand for a more responsive launch system tailored for small satellites, and on the UK’s interest in developing a spaceport and national expertise in space access. The core members of the consortium responsible for the technical design also include BAE Systems, Fluid Gravity Engineering and the University of Glasgow.
The system optimisation work requires a high performance computing cluster in order to efficiently analyse the large amount of mission and design options, and to ensure a good understanding of the trade-offs between all the optimisation variables, from the vehicle design parameters to the openloop control law.
On a more technical level, the work focuses on different approaches for global and local optimisation using a direct, multi-phase approach for the trajectory for both single and many objective problems. The main tools are: MPA-IDEA, a multi-population adaptive inflationary differential evolution algorithm for global optimisation, MACS, a multi-agent collaborative search >lgorithm for multi/many-objective problems, and two local, gradient-based optimisation approaches, one using multi-shooting (TROPICO) while the other uses collocation through direct finite elements in time (MODOC).
For more information about the project contact Dr Christie Maddock (firstname.lastname@example.org), Lecturer at the Department of Mechanical and Aerospace Engineering at the University of Strathclyde,
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