Adaptive control for High performance Astronomy


Staff Mentor:

prof.dr.ir. M. Verhaegen (Michel)


Other Mentor(s):

N.J. Doelman (TNO)

Keywords:

Adaptive and learning control; Distributed control; Imaging and adaptive optics

Description:

TNO and DCSC have developed an innovative manner to improve the control performance of Adaptive Optics Systems. This innovative includes the temporal dynamics of the aberrations. The goal of the thesis is to validate this new control concept on real-life dat.

The principle of adaptive optics, consider Figure 1. A light beam emerging from a distant star has a perfectly flat wavefront when it arrives at the outer layers of the atmosphere. As the beam travels through the atmosphere however, refractive index inhomogeneities cause some parts of the beam to be delayed with respect to others.At the time that the light beam arrives at the telescope aperture, the wavefront is distorted to such an extent that the angular resolution in the visible is equivalent to a telescope with a diameter of 10-20cm. To reduce the wavefront distortions and by that increase the resolution of the telescope, an adaptive optics system measures the wavefront aberrations. These measurements are subsequently used in a feedback scheme to control the deformable mirror. The mirror should be actuated in such a way that it restores the original wavefront by canceling out the distortion. Finally, a camera can record the corrected light beam.Even though the principle of adaptive optics seems to be quite simple, it is a challenging field for control engineering. In collaboration with TNO, the master thesis student will develop his own adaptive controller scheme based on the pioneering work of Prof. Gibson of the university of California, Los Angeles and test this implementation on a prototype structure. The student has an interest in advanced control engineering methods and their operation in high-technology driven applications.



Schematic representation of an adaptive optics system

© Copyright Delft Center for Systems and Control, Delft University of Technology, 2017.