Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers

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Abstract

In this study, a neuro-fuzzy controller (NFC) was developed for spacecraft attitude control to mitigate large computational load of the state-dependent Riccati equation (SDRE) controller. The NFC was developed by training a neuro-fuzzy network to approximate the SDRE controller. The stability of the NFC was numerically verified using a Lyapunov-based method, and the performance of the controller was analyzed in terms of approximation ability, steady-state error, cost, and execution time. The simulations and test results indicate that the developed NFC efficiently approximates the SDRE controller, with asymptotic stability in a bounded region of angular velocity encompassing the operational range of rapid-attitude maneuvers. In addition, it was shown that an approximated optimal feedback controller can be designed successfully through neuro-fuzzy approximation of the optimal open-loop controller.

Original languageEnglish
Pages (from-to)137-152
Number of pages16
JournalAdvances in Space Research
Volume57
Issue number1
DOIs
Publication statusPublished - 2016

Bibliographical note

Funding Information:
This work was supported by the Space Core Technology Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning of Republic of Korea ( 2013M1A3A3A02042448 ). This research was also supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education of Republic of Korea ( 2013R1A1A2013091 ).

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Astronomy and Astrophysics
  • Geophysics
  • Atmospheric Science
  • Space and Planetary Science
  • Earth and Planetary Sciences(all)

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