A closed-loop control method and system of a wavefront-sensorless adaptive optical system
By acquiring focal plane PSF images using a scientific camera, and using a residual wavefront estimation neural network and an autoregressive prediction model for rapid estimation, combined with non-integer frame delay compensation and a constrained model prediction controller, the hardware complexity and correction lag problems of traditional adaptive optics systems are solved, achieving stable real-time correction and high-quality imaging under strong turbulence conditions.
Patent Information
- Application Number
- CN202610840076.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-11
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional adaptive optics systems suffer from complex hardware, non-common-path aberrations, measurement difficulties under low-photon conditions, latency sensitivity under high-speed dynamic turbulence, insufficient speed estimation by wavefront-less sensing methods, failure to consider time delays in deep learning methods, and lack of constraints in deformable mirror control, resulting in correction lag and insufficient stability.
A scientific camera is used to acquire focal plane PSF images. The residual wavefront estimation neural network and online autoregressive prediction model are used for rapid estimation. Combined with non-integer frame delay compensation and constrained model predictive controller, control commands that meet the deformable mirror constraints are generated to achieve stable real-time correction.
It improves the real-time performance and stability of correction under strong turbulence conditions, reduces correction lag, and enhances the quality of imaging and communication light spots.
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Figure CN122411068A_ABST