【摘要】 将模糊神经网络控制引入到三轴稳定卫星的姿态控制中,结合Q-学习和BP神经网络来解决模糊神经网络参数在线调整问题,在无需训练样本的前提下实现控制器的在线学习.仿真结果表明,这种基于Q-学习的模糊神经网络控制不仅可以满足对姿态控制精度的要求,还有效地抵制了外界干扰,提高了姿态稳定度,对卫星的不确定性有较强的鲁棒性.更多还原

【Abstract】 A fuzzy neural control approach applied to the three-axis stabilized satellite is presented.In order to solve the problems of online learning and tuning of the fuzzy neural network parameters,the method of Q-learning combined with BP neural network is proposed and studied so that the training samples for the selflearning controller are not needed.Simulation results showed that the proposed control method with Q reinforcement learning architecture could not only improve the accuracy,(stability) and(robustness) of the system,but also deal with uncertainties and external disturbance efficiently.更多还原