Optimizing low-thrust gravity assist interplanetary trajectories using evolutionary neurocontrollers

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)

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
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 > Aerospace Sciences
Publisher:IEEE Computer Society
ISBN:9781424413409

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