FPGA-accelerated adaptive optics wavefront control part II

We present progressive work that is based on our recently developed rapid control prototyping system (RCP), designed for the implementation of high-performance adaptive optical control algorithms using a continuous de-formable mirror (DM). The RCP system, presented in 2014, is resorting to a Xilinx Kintex-7 Field Programmable Gate Array (FPGA), placed on a self-developed PCIe card, and installed on a high-performance computer that runs a hard real-time Linux operating system. For this purpose, algorithms for the efficient evaluation of data from a Shack-Hartmann wavefront sensor (SHWFS) on an FPGA have been developed. The corresponding analog input and output cards are designed for exploiting the maximum possible performance while not being constrained to a specific DM and control algorithm due to the RCP approach. In this second part of our contribution, we focus on recent results that we achieved with this novel experimental setup. By presenting results which are far superior to the former ones, we further justify the deployment of the RCP system and its required time and resources. We conducted various experiments for revealing the effective performance, i.e. the maximum manageable complexity in the controller design that may be achieved in real-time without performance losses. A detailed analysis of the hidden latencies is carried out, showing that these latencies have been drastically reduced. In addition, a series of concepts relating the evaluation of the wavefront as well as designing and synthesizing a wavefront are thoroughly investigated with the goal to overcome some of the prevalent limitations. Furthermore, principal results regarding the closed-loop performance of the low-speed dynamics of the integrated heater in a DM concept are illustrated in detail; to be combined with the piezo-electric high-speed actuators in the next step

[1]  R. Tyson Principles of Adaptive Optics, Third Edition , 2010 .

[2]  Daniel G Smith,et al.  Generalized method for sorting Shack-Hartmann spot patterns using local similarity. , 2008, Applied optics.

[3]  Claudia Reinlein,et al.  Manufacturing and Characterization of a Deformable Membrane with Integrated Temperature Sensors and Heating Structures in Low Temperature Co‐fired Ceramics , 2013 .

[4]  Donald G. Bailey,et al.  Design for Embedded Image Processing on FPGAs , 2011 .

[5]  Huibert Kwakernaak,et al.  Linear Optimal Control Systems , 1972 .

[6]  Phillip Bedggood,et al.  Comparison of sorting algorithms to increase the range of Hartmann-Shack aberrometry. , 2010, Journal of biomedical optics.

[7]  J. Reger,et al.  ADAPTIVE OPTICS CONTROL FOR LASER MATERIAL PROCESSING , 2012 .

[8]  Johann Reger,et al.  Application of μ-synthesis based H∞-control for adaptive optics in laser material processing , 2013, 2013 IEEE International Conference on Control Applications (CCA).

[9]  Johann Reger,et al.  Real-time implementation of the spiral algorithm for Shack-Hartmann wavefront sensor pattern sorting on an FPGA , 2016 .

[10]  Claudia Reinlein,et al.  Testing of thermally piezoelectric deformable mirror with buried functionality , 2014, Photonics West - Micro and Nano Fabricated Electromechanical and Optical Components.

[11]  François Le Gall,et al.  Powers of tensors and fast matrix multiplication , 2014, ISSAC.

[12]  Robert K. Tyson Principles of Adaptive Optics , 1991 .

[13]  A. Tünnermann,et al.  FPGA-accelerated adaptive optics wavefront control , 2014, Photonics West - Micro and Nano Fabricated Electromechanical and Optical Components.

[14]  Johann Reger,et al.  Real-Time Spot Detection and Ordering for a Shack–Hartmann Wavefront Sensor With a Low-Cost FPGA , 2014, IEEE Transactions on Instrumentation and Measurement.