Ultra-high contrast imaging in space is essential for the direct imaging detection of Earth-like planets, the achievement of which depends on the precise control of the optical wavefront by the space coronagraph system, and therefore requires the development of specialized on-orbit algorithms dedicated to wavefront detection and correction. While such algorithms have been widely used in ground-based adaptive optics systems, but in space, they cannot be designed based on pure CPU computing due to the limitations of space CPU performance and selection. Based on the hybrid architecture of FPGA and CPU, the wavefront correction is realized, which is capable of locking the high-contrast imaging dark region required for exoplanet detection while taking into account the hardware resources and computing accuracy. The algorithm of the above hybrid architecture also has a significant speed advantage in large-scale adaptive optics systems, and the wavefront processing delay is shortened by 1281.826 μs for a 100×100 sub-aperture adaptive optics system, which can meet the demand for high-speed parallel computation of the adaptive optics systems, such as the ExAO, the GLAO, and the MCAO, which are equipped with the ground-based large-aperture telescopes.