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Crew exploration vehicle (CEV) attitude control using a neural–immunology/memory network

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  • Liguo Weng
  • Min Xia
  • Wei Wang
  • Qingshan Liu

Abstract

This paper addresses the problem of the crew exploration vehicle (CEV) attitude control. CEVs are NASA's next-generation human spaceflight vehicles, and they use reaction control system (RCS) jet engines for attitude adjustment, which calls for control algorithms for firing the small propulsion engines mounted on vehicles. In this work, the resultant CEV dynamics combines both actuation and attitude dynamics. Therefore, it is highly nonlinear and even coupled with significant uncertainties. To cope with this situation, a neural–immunology/memory network is proposed. It is inspired by the human memory and immune systems. The control network does not rely on precise system dynamics information. Furthermore, the overall control scheme has a simple structure and demands much less computation as compared with most existing methods, making it attractive for real-time implementation. The effectiveness of this approach is also verified via simulation.

Suggested Citation

  • Liguo Weng & Min Xia & Wei Wang & Qingshan Liu, 2015. "Crew exploration vehicle (CEV) attitude control using a neural–immunology/memory network," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(1), pages 152-158, January.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:1:p:152-158
    DOI: 10.1080/00207721.2013.775389
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    References listed on IDEAS

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    1. M.K. Singh & D.R. Parhi, 2011. "Path optimisation of a mobile robot using an artificial neural network controller," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(1), pages 107-120.
    2. Wen Yu & Kang Li & Xiaoou Li, 2011. "Automated nonlinear system modelling with multiple neural networks," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(10), pages 1683-1695.
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