Simulation of Wavefront-based Disturbance Observers for Large Telescopes
Abstract
The performance of future observatories such as the Extremely Large Telescope is mainly limited by atmospheric turbulence and structural vibrations of the optical assembly. To further enhance the mitigation performance of adaptive optics, real-time information about the disturbances acting on the control loop is needed. Current systems therefore employ a combination of wavefront sensor- and accelerometer-based filters. In this work, methods using only data from natural- and laser guide star (NGS, LGS) measurements are presented, as telescopes like the Very Large Telescope already have multiple fast and high-resolution wavefront sensors installed. This approach also avoids the costly installation and operation of additional accelerometers on the optical elements. We introduce two innovative disturbance observer schemes to sense both turbulence and vibration information. A multi-rate estimator for atmospheric influences is based on Kalman filter theory and can incorporate NGS and LGS signals at different loop rates. The estimator for structural perturbations uses Gaussian process regression and can be implemented in an offline and online configuration. We validate the filter designs with data from a realistic end-to-end adaptive optics model with randomly generated turbulence and vibrations. The simulation is fed with on-sky data from the Adaptive Optics Facility of the Very Large Telescope. The presented disturbance observer schemes demonstrate promising results and may be considered as potential alternatives or extensions to existing techniques such as linear-quadratic controllers with Kalman filtering (LQG).