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ESO has developed a concept for a compact laser guide star unit for use in future Adaptive Optics (AO) systems. A small powerful laser is combined with a telescope that launches the beam, creating a single modular unit that can be mounted directly on a large telescope. This approach solves several of the stability problems experienced with a number of first generation laser guide star systems around the world. Four of these compact laser guide stars will be used for the new VLT 4LGSF Adaptive Optics Facility (AOF), to be installed on UT4 in Paranal. The design is passively athermalized over a large temperature range as well as under the influence of thermal gradients. TNO has developed the laser launch telescopes and successfully demonstrated its performance under operational conditions. The technology will also serve as a testbed ahead of the construction of the future European Extremely Large Telescope, which will also have multiple laser guide star units.

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.

Even though the wavefront distortion introduced by atmospheric turbulence is a dynamic process, its temporal evolution is usually neglected in the adaptive optics (AO) control design. Most AO control systems consider only the spatial correlation in a separate wavefront reconstruction step. By accounting for the temporal evolution of the wavefront it should be possible to further reduce the residual phase error and enable the use of fainter guide stars. Designing a controller that takes full advantage of the spatio-temporal correlation in the wavefront requires a detailed model of the wavefront distortion. In this paper we present a dedicated subspace identification algorithm that is able to provide the required prior knowledge. On the basis of open-loop wavefront slope data it estimates a multi-variable state-space model of the wavefront disturbance. The model provides a full description of the spatio-temporal statistics in a form that is suitable for control. The algorithm is demonstrated on open-loop wavefront data.

The problem of finding the closed-loop optimal controller is formulated in an H2-optimal control framework. This provides a natural way to account for the fact that in many AO systems the wavefront phase cannot be measured directly. Given a multi-variable disturbance model of both wavefront slopes and wavefront phases,3 this provides a general procedure to compute the closed-loop controller. If the wavefront sensor and deformable mirror are static and the only dynamics in the system is a unit-sample delay between measurement and correction, an analytical expression for the optimal controller can be derived. This results in a control approach, in which both identification and computation of the optimal controller are exclusively based on standard matrix operations. No Riccati equation needs to be solved to compute the optimal controller. The proposed H2-control approach is numerically validated on open-loop wavefront sensor data and its performance is compared with the common approach. Also the sensitivity to measurement noise is considered.

The field of exoplanet research is rapidly advancing through the development of new technology, observing techniques, and post-processing methods. In the last 30 years, thousands of exoplanet candidates have been found through various methods. These discoveries have revealed a zoo of exoplanetary systems looking very different from our own Solar System. This dissertation contains two very distinctive parts, both related to the measurement of exoplanetary systems.The first part of this dissertation, Chapter 2, investigates 8 light curves found in the Kepler data archive. These light curves show periodic brightening events that look different from a normal exoplanet signal. The second part of this dissertation, focuses on high-contrast imaging (HCI). Current HCI instruments are more sensitive to exoplanets orbiting far out from their host star. To probe the regions close-in to the star, the extreme adaptive optics (XAO) subsystem needs to improve in performance. Specifically, the XAO does not correct well enough for the continuous evolution of turbulence during the time it takes the XAO to measure the phase and subsequently correct for the aberrations (resulting in the servo-lag error). This dissertation focuses on data-driven predictive control to address the servo-lag error.