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)

Abstract

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
• Status: Published
• Refereed: Yes
• 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 > Autonomous Systems and Connectivity
• Journal Name: Journal of Guidance, Control, and Dynamics
• Publisher: American Institute of Aeronautics and Astronautics
• ISSN: 0731-5090
• ISSN (Online): 1533-3884