Macdonald, Malcolm (2005) Analytical methodologies for solar sail trajectory design. PhD thesis, University of Glasgow.
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Abstract
With increased international interest in solar sailing for future science missions comes the requirement to generate algorithms for effective orbit design, manoeuvring and control. Previously unexplained seasonal variations in sail escape times from Earth orbit are explained analytically and corroborated within a numerical trajectory model. Simple blended sail control algorithms are developed which are explicitly independent of time and provide near optimal planetary escape trajectories, while maintaining a safe minimum altitude. It is also shown that the time until escape corresponding to the minimum sail acceleration requirement for shadow free Earth escape is independent of initial altitude. Traditional trajectory optimisation methods are computationally intensive, requiring significant engineering judgement and experience. A new method of blending locally optimal control laws is thus developed for more complex applications. Each control law is prioritised by consideration of how efficiently it will use the solar sail and how far each orbital element is from its target value. The blended, locally optimal sail thrust vector is thus defined to use the sail efficiently, allowing the rapid generation of near-optimal trajectories. The blending method introduced is demonstrated for a complex orbit transfer about Mercury and for two planet-centred station keeping applications. The new method is also demonstrated for three different heliocentric scenarios and is shown to closely match, or even out-perform some existing optimization methods. Furthermore, the method is demonstrated as suitable for rapid mission analysis with an ideal, a non-ideal or optical degradation solar sail force model, while also providing an excellent initial guess for other optimisation methods. The blending algorithms used are explicitly independent of time and as such the control systems are suitable as on-board sail controllers.
Item Type: | Thesis (PhD) |
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Qualification Level: | Doctoral |
Additional Information: | Adviser: Prof. Colin McInnes. |
Keywords: | Aerospace engineering. |
Colleges/Schools: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
Supervisor's Name: | Supervisor, not known |
Date of Award: | 2005 |
Depositing User: | Enlighten Team |
Unique ID: | glathesis:2005-71152 |
Copyright: | Copyright of this thesis is held by the author. |
Date Deposited: | 10 May 2019 10:49 |
Last Modified: | 25 Aug 2021 10:03 |
Thesis DOI: | 10.5525/gla.thesis.71152 |
URI: | https://theses.gla.ac.uk/id/eprint/71152 |
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