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 language | English |
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Pages (from-to) | 313-316+326 |
Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
Volume | 23 |
Issue number | 3 |
Publication status | Published - 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.