Artificial neural networks for multiple NEA rendezvous missions with continuous thrust

Viavattene, G. and Ceriotti, M. (2022) Artificial neural networks for multiple NEA rendezvous missions with continuous thrust. Journal of Spacecraft and Rockets, 59(2), pp. 574-586. (doi: 10.2514/1.A34799)

Abstract

The interest for near-Earth asteroids for scientific studies and, in particular, for potentially hazardous asteroids requires the space community to perform multiple-asteroid missions with close-up observations. To this end, multiple near-Earth asteroid rendezvous missions can help reduce the cost of the mission. Given the enormous number of asteroids, this work proposes a method based on artificial neural networks (ANNs) to quickly estimate the transfer time and cost between asteroids using low-thrust propulsion. The neural network output is used in a sequence search algorithm based on a tree-search method to identify feasible sequences of asteroids to rendezvous. The rendezvous sequences are optimized by solving an optimal control problem for each leg to verify the feasibility of the transfer. The effectiveness of the presented methodology is assessed through sequences of asteroids of interest optimized using two low-thrust propulsion systems, namely solar electric propulsion and solar sailing. The results show that ANNs are able to estimate the duration and cost of low-thrust transfers with high accuracy in a modest computational time.

• Item Type: Articles
• Additional Information: Giulia Viavattene gratefully acknowledges the support received for this research from the James Watt School of Engineering at the University of Glasgow for funding the research under the James Watt sponsorship program.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Viavattene, Giulia and Ceriotti, Dr Matteo
• Authors: Viavattene, G., and Ceriotti, M.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: Journal of Spacecraft and Rockets
• Publisher: American Institute of Aeronautics and Astronautics
• ISSN: 0022-4650
• ISSN (Online): 1533-6794
• Published Online: 15 November 2021
• Copyright Holders: Copyright © 2021 American Institute of Aeronautics and Astronautics, Inc.
• First Published: First published in Journal of Spacecraft and Rockets 59(2):574-586
• Publisher Policy: Reproduced in accordance with the publisher copyright policy