Carnelli, I., Dachwald, B. and Vasile, M. (2008) Optimizing low-thrust gravity assist interplanetary trajectories using evolutionary neurocontrollers. In: 2007 IEEE Congress on Evolutionary Computation, CEC 2007. IEEE Computer Society: Piscataway, NJ, pp. 965-972. ISBN 9781424413409 (doi: 10.1109/CEC.2007.4424574)
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Abstract
The combination of low-thrust propulsion and gravity assists allows designing high-energy missions. However the optimization of such trajectories is no trivial task. In this paper, we present a novel method that is based on evolutionary neurocontrollers. The main advantage of using a neurocontroller is the generation of a control law with a limited number of decision variables. On the other hand the evolutionary algorithm allows to look for globally optimal solutions more efficiently than a systematic search. In addition, a steepest ascent algorithm is introduced that acts as a navigator during the planetary encounter, providing the neurocontroller with the optimal insertion parameters. Results are presented for a Mercury rendezvous with a Venus gravity assist and for a Pluto flyby with a Jupiter gravity assist
Item Type: | Book Sections |
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Additional Information: | 2007 IEEE Congress on Evolutionary Computation, CEC 2007, September 25, 2007 - September 28, 2007, Singapore |
Status: | Published |
Glasgow Author(s) Enlighten ID: | UNSPECIFIED |
Authors: | Carnelli, I., Dachwald, B., and Vasile, M. |
College/School: | College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity |
Publisher: | IEEE Computer Society |
ISBN: | 9781424413409 |
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