Modeling of Segmented Primary Mirror Surface Control System for Space-based Telescope

The segmented primary mirror of next generation space-based telescope was controlled by a number of actuators to achieve a required surface shape. The back-propagation (BP) neural network was applied to modeling the primary mirror surface with inputs of actuator applied force and outputs of Zernike polynomial coefficient. By using primary mirror finite element analysis data, BP model was trained offline and its predictive precision was verified. The simulation results show that the precision of BP neural network model is approximate to the finite element analysis, and it satisfies the requirement of space-based telescope real-time control.