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

Research output: Contribution to journalArticle

13 Citations (Scopus)

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 Jan 1

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attitude control
Attitude control
Spacecraft
controllers
spacecraft
Controllers
approximation
Riccati equation
Riccati equations
cost
simulation
maneuvers
Angular velocity
angular velocity
Asymptotic stability
education
costs
Feedback

All Science Journal Classification (ASJC) codes

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

Cite this

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Spacecraft attitude control using neuro-fuzzy approximation of the optimal controllers. / Kim, Sung Woo; Park, Sang-Young; Park, Chandeok.

In: Advances in Space Research, Vol. 57, No. 1, 01.01.2016, p. 137-152.

Research output: Contribution to journalArticle

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