Evolutionary neurocontrol: a novel method for low-thrust gravity-assist trajectory optimization

Carnelli, I., Dachwald, B. and Vasile, M. (2009) Evolutionary neurocontrol: a novel method for low-thrust gravity-assist trajectory optimization. Journal of Guidance, Control, and Dynamics, 32(2), pp. 616-625. (doi: 10.2514/1.32633)

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Publisher's URL: http://dx.doi.org/10.2514/1.32633


The combination of low-thrust propulsion and gravity assists to enhance deep-space missions has proven to be a remarkable task. In this paper, we present a novel method that is based on evolutionary neurocontrollers. The main advantage in the use of a neurocontroller is the generation of a control law with a limited number of decision variables. On the other hand, the evolutionary algorithm allows one to look for globally optimal solutions more efficiently than with 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:Articles
Glasgow Author(s) Enlighten ID:Vasile, Dr Massimiliano
Authors: Carnelli, I., Dachwald, B., and Vasile, M.
College/School:College of Science and Engineering > School of Engineering > Aerospace Sciences
Journal Name:Journal of Guidance, Control, and Dynamics
Publisher:American Institute of Aeronautics and Astronautics
ISSN (Online):1533-3884

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