Data-driven subspace predictive control of adaptive optics for high-contrast imaging

Data-Driven Optimal Control for Adaptive Optics

Limits of Adaptive Optics for high contrast imaging

The effects of photon noise, aliasing, wavefront chromaticity and scintillation on the point spread function (PSF) contrast achievable with ground based adaptive optics (AO) are evaluated for different wavefront sensing schemes. I show that a wavefront sensor (WFS) based upon the Zernike phase contrast technique offers the best sensitivity to photon noise at all spatial frequencies, while the S...

Advancing High - Contrast Adaptive Optics

A long-standing challenge has been to directly image faint extrasolar planets adjacent to their host suns, which may be 10 – 10 times brighter than the planet. Several extreme AO systems designed for high-contrast observations have been tested at this point, including SPHERE, Magellan AO, PALM-3000, Project 1640, NICI, and the Gemini Planet Imager (GPI). The GPI is the world’s most advanced hig...

High Contrast Imaging with Polycapillary Optics

Polycapillary x-ray optics provide an innovative new way to control x-ray beams. Placing these optics after the object to be imaged provides very efficient rejection of Compton scatter, while allowing image magnification without loss of resolution, image demagnification, or image shaping to match with digital detectors. An extensive study of the effects of surface and profile defects have great...

Data-driven Direct Adaptive Model Based Predictive Control

This paper is concerned with the design of Direct Adaptive Model Based Predictive Control (DAMBPC) using subspace identification technique to identify and implement the controller parameters. The direct identification of controller parameters reduces the design effort and computation load which is usually involved with classical adaptive control techniques. The proposed method requires a single...