Trajectory generation for autonomous unmanned aircraft using inverse dynamics

dc.contributor.advisorTsourdos, Antonios
dc.contributor.advisorCooke, Alastair K.
dc.contributor.authorDrury, R. G.
dc.date.accessioned2011-06-24T14:44:48Z
dc.date.available2011-06-24T14:44:48Z
dc.date.issued2010-09
dc.description.abstractThe problem addressed in this research is the in-flight generation of trajectories for autonomous unmanned aircraft, which requires a method of generating pseudo-optimal trajectories in near-real-time, on-board the aircraft, and without external intervention. The focus of this research is the enhancement of a particular inverse dynamics direct method that is a candidate solution to the problem. This research introduces the following contributions to the method. A quaternion-based inverse dynamics model is introduced that represents all orientations without singularities, permits smooth interpolation of orientations, and generates more accurate controls than the previous Euler-angle model. Algorithmic modifications are introduced that: overcome singularities arising from parameterization and discretization; combine analytic and finite difference expressions to improve the accuracy of controls and constraints; remove roll ill-conditioning when the normal load factor is near zero, and extend the method to handle negative-g orientations. It is also shown in this research that quadratic interpolation improves the accuracy and speed of constraint evaluation. The method is known to lead to a multimodal constrained nonlinear optimization problem. The performance of the method with four nonlinear programming algorithms was investigated: a differential evolution algorithm was found to be capable of over 99% successful convergence, to generate solutions with better optimality than the quasi- Newton and derivative-free algorithms against which it was tested, but to be up to an order of magnitude slower than those algorithms. The effects of the degree and form of polynomial airspeed parameterization on optimization performance were investigated, and results were obtained that quantify the achievable optimality as a function of the parameterization degree. Overall, it was found that the method is a potentially viable method of on-board near- real-time trajectory generation for unmanned aircraft but for this potential to be realized in practice further improvements in computational speed are desirable. Candidate optimization strategies are identified for future research.en_UK
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/5583
dc.language.isoenen_UK
dc.publisherCranfield Universityen_UK
dc.rights© Cranfield University 2010. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner.en_UK
dc.subjectAutonomyen_UK
dc.subjectdifferential evolutionen_UK
dc.subjectdirect methodsen_UK
dc.subjectinverse dynamicsen_UK
dc.subjectnear-real-timeen_UK
dc.subjectnegative-gen_UK
dc.subjectnonlinear programmingen_UK
dc.subjectnumerical optimizationen_UK
dc.subjectoptimal controlen_UK
dc.subjectquaternionsen_UK
dc.subjecttrajectory generationen_UK
dc.subjectUAVen_UK
dc.subjectunmanned aircraften_UK
dc.titleTrajectory generation for autonomous unmanned aircraft using inverse dynamicsen_UK
dc.typeThesis or dissertationen_UK
dc.type.qualificationlevelDoctoralen_UK
dc.type.qualificationnamePhDen_UK

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