On-Line Fuzzy Neural Control of Satellite Attitude Based on Q-Learning

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.