Neuro-fuzzy control of satellite attitude by reinforcement learning

Ping Guan*, Xing Qiao Liu, Jia Bin Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Neuro-fuzzy controller with reinforcement learning is applied in the attitude control of satellites. The detailed design method is presented and the algorithm of reinforcement learning is deduced. Parameters of the controller are adjusted only by reinforcement signal, but not by the learning sample. Simulation results show that the method can effectively copy with the uncertainty of satellite and thus posses good robustness. Under the proposed method, higher precision of attitude control of satellite can be achieved.

Original languageEnglish
Pages (from-to)313-316+326
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume23
Issue number3
Publication statusPublished - Jun 2003

Keywords

  • Attitude control
  • Neural network
  • Neuro-fuzzy control
  • Reinforcement learning

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Guan, P., Liu, X. Q., & Chen, J. B. (2003). Neuro-fuzzy control of satellite attitude by reinforcement learning. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 23(3), 313-316+326.