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KIAM Preprint № 269, Moscow, 2018
Authors: Sorokin A.V., Shirobokov M.G.
Artificial neural networks for low-thrust spacecraft control
In this work, two artificial neural networks aimed at low-thrust spacecraft control are designed. One of the networks is called the controlling network; the another is called the predictive network. The controlling network is learned to solve the optimal control problem between two phase vectors. The predictive network is learned to propagate solutions of the extended equations of motion (prime and dual variables of the Pontryagin's maximum principle). The proposed networks can be used for orbital correction near a nominal regime. The architecture of the networks as well as sample construction process and learning methods are described. Simulation results are provided.
artificial neural network, low thrust, orbital motion, Pontryagin’s maximum principle
Publication language: russian,  pages: 31
Research direction:
Theoretical and applied problems of mechanics
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About authors:
  • Sorokin Artemiy Vladimirovich,  ,  Московский физико-технический институт
  • Shirobokov Maksim Gennadievich, RAS