Search

Most adaptive optics systems (AO) are based on a simple control law that is unable to account for the temporal evolution of the wavefront. In this paper, a recently proposed data-driven H2-optimal control approach is demonstrated on an AO laboratory setup. The proposed control approach does not assume any form of decoupling and can therefore exploit the spatio-temporal correlation in the wavefront. The performance of the optimal control approach is compared with a conventional method. An analysis of the dominant error sources shows that the optimal control approach leads to a significant reduction in the temporal error. Since the temporal error grows with the Greenwood to sampling frequency ratio, the performance gain is especially large at large ratios.

Most adaptive optics systems (AO) are based on a simple control law that is unable to account for the temporal evolution of the wavefront. In this paper, a recently proposed data-driven H2-optimal control approach is demonstrated on an AO laboratory setup. The proposed control approach does not assume any form of decoupling and can therefore exploit the spatio-temporal correlation in the wavefront. The performance of the optimal control approach is compared with a conventional method. An analysis of the dominant error sources shows that the optimal control approach leads to a significant reduction in the temporal error. Since the temporal error grows with the Greenwood to sampling frequency ratio, the performance gain is especially large at large ratios.