卫星姿态再励学习的模糊神经控制

将再励学习的模糊神经控制引入卫星姿态控制中，给出详尽的实现方法，推导了模糊神经控制器的自学习算法．直接利用再励信号，对控制器的参数进行在线调节，不需要控制器的学习样本．仿真结果表明该控制算法能有效地克服卫星的不确定性，具有较强的鲁棒性，可实现较高精度的卫星姿态控制．

Neuro-Fuzzy Control of Satellite Attitude by Reinforcement Learning

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.