High-Performance Control and Prediction for Adaptive Optics

Atmospheric turbulence presents a major obstacle to maintaining the fidelity of high-energy laser beams over extended distances. Classical control methods, such as proportional-integral controllers, often struggle to mitigate broadband atmospheric aberrations as they do not addressthe loop latency inherent to adaptive optics systems. Without a form of wavefront prediction, there is no method to increase the bandwidth of these controllers other than increasing the sampling frequency.;This dissertation presents two adaptive optics methods to predict and control wavefront aberrations, and adaptive optics controller bandwidth without an increased sampling frequency. The first is an optimal linear time-invariant controller constructed from a state-space model of the turbulence flow. The second control method is an adaptive controller, based on a recursive least squares lattice filter, that tracks the aberrations statistics during operation. Both control methods have the form of multichannel prediction filters that capture the statistics of the aero-optical turbulence to mitigate latency in the adaptive optics loop.;The performance of these control schemes versus classical integrator methods is investigated in an adaptive optics experiment that accurately mimics large-scale adaptive optics systems. Similar methods have been successfully employed to mitigate long-range atmospheric turbulence with constant power spectrums, while the experiments here examine controller performance against disturbances derived from recent in-flight measurements of aero-optical turbulence.;Experimental results show significant improvement in wavefront correction achieved by both prediction methods versus classical control methods. Altering the flow characteristics of the disturbance wavefront during the control process illustrates the ability of the adaptive controller to track changes in the aberration statistics.