Iterative Learning Disturbance Observer Based Attitude Stabilization of Flexible Spacecraft Subject to Complex Disturbances and Measurement Noises

To realize high-precision attitude stabilization of a flexible spacecraft in the presence of complex disturbances and measurement noises, an iterative learning disturbance observer (ILDO) is presented in this paper. Firstly, a dynamic model of disturbance is built by augmenting the integral of the lumped disturbance as a state. Based on it, ILDO is designed by introducing iterative learning structures. Then, comparative analyses of ILDO and traditional disturbance observers are carried out in frequency domain. It demonstrates that ILDO combines the advantages of high accuracy in disturbance estimation and favorable robustness to measurement noise. After that, an ILDO based composite controller is designed to stabilize the spacecraft attitude. Finally, the effectiveness of the proposed control scheme is verified by simulations.

Automated summary

An iterative learning disturbance observer (ILDO) is proposed in this paper to achieve high-precision attitude stabilization of a flexible spacecraft in the presence of complex disturbances and measurement noises. The ILDO combines the advantages of high accuracy in disturbance estimation and favorable robustness to measurement noise. The effectiveness of the proposed control scheme is verified through simulations.