Attitude Control Based on Neural Networks for Micro Aerial Vehicle with Flapping Wings

For attitude control of micro aerial vehicle with flapping wings, a control method based on BP(backpropagation) neural networks and average moments is proposed. At the end of each wingbeat, the neural network controller determines the adjustment value of attack angle according to attitude errors. The micro vehicle obtains desired average moments which control attitude at next wingbeat. The proposed controller is simulated. The results show that the control system is robust.