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Future large telescopes, such as E-ELT and TMT, will need feedback control of the thousands of actuators underneath their segmented primary mirrors (M1). Differences in actuator dynamics and spatially and temporally changing disturbances make it extremely diffcult to formulate classical controllers which are both suffciently robust and highly performing. Therefore, TNO has developed and tested a control approach, in which the actual system response is quickly measured, disturbances are continuously estimated and the controller is adapted in real-Time. The algorithm is tested on an actual M1-relevant setup, in which it converges to a sub-nm optimum within a few minutes, keeps track of changing disturbances and shows its reliability over multiple days.

One of the key limitations of the direct imaging of exoplanets at small angular separations are quasi-static speckles that originate from evolving non-common path aberrations (NCPA) to which the primary adaptive optics system is inherently blind. The main focus of this thesis is the development and (on-sky) testing of integrated coronagraph and focal-plane wavefront-sensing solutions to deal with NCPA. First, we enable focal-plane wavefront sensing with vector-Apodizing Phase Plate coronagraph by integrating a pupil-plane amplitude asymmetry into the design. Low-order wavefront sensing is then demonstrated with a non-linear model-based algorithm and high-order wavefront with spatial Linear Dark Field Control. We introduce the polarization-encoded self-coherent camera, which is a new and more powerful variant of the self-coherent camera. Furthermore, we show through on-sky tests that the “Fast and Furious” focal-plane wavefront sensing algorithm is capable of measured and controlling the low-wind effect. Lastly, the vector speckle grid is presented and dramatically increases the signal-to-noise ration of exoplanet variability measurements. The ultimate goal of this thesis is to enable the direct imaging and characterization of rocky exoplanets with future extremely large telescopes.

One of the key limitations of the direct imaging of exoplanets at small angular separations are quasi-static speckles that originate from evolving non-common path aberrations (NCPA) to which the primary adaptive optics system is inherently blind. The main focus of this thesis is the development and (on-sky) testing of integrated coronagraph and focal-plane wavefront-sensing solutions to deal with NCPA. First, we enable focal-plane wavefront sensing with vector-Apodizing Phase Plate coronagraph by integrating a pupil-plane amplitude asymmetry into the design. Low-order wavefront sensing is then demonstrated with a non-linear model-based algorithm and high-order wavefront with spatial Linear Dark Field Control. We introduce the polarization-encoded self-coherent camera, which is a new and more powerful variant of the self-coherent camera. Furthermore, we show through on-sky tests that the “Fast and Furious” focal-plane wavefront sensing algorithm is capable of measured and controlling the low-wind effect. Lastly, the vector speckle grid is presented and dramatically increases the signal-to-noise ration of exoplanet variability measurements. The ultimate goal of this thesis is to enable the direct imaging and characterization of rocky exoplanets with future extremely large telescopes.

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.