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@InProceedings{kim:icalepcs2019-tucpl02,
author = {M. Kim and S.M. Ammons and B. Hackel and L. Poyneer},
title = {{Processing System Design for Implementing a Linear Quadratic Gaussian (LQG) Controller to Optimize the Real-Time Correction of High Wind-Blown Turbulence}},
booktitle = {Proc. ICALEPCS'19},
pages = {761--766},
paper = {TUCPL02},
language = {english},
keywords = {controls, software, real-time, optics, Linux},
venue = {New York, NY, USA},
series = {International Conference on Accelerator and Large Experimental Physics Control Systems},
number = {17},
publisher = {JACoW Publishing, Geneva, Switzerland},
month = {08},
year = {2020},
issn = {2226-0358},
isbn = {978-3-95450-209-7},
doi = {10.18429/JACoW-ICALEPCS2019-TUCPL02},
url = {https://jacow.org/icalepcs2019/papers/tucpl02.pdf},
note = {https://doi.org/10.18429/JACoW-ICALEPCS2019-TUCPL02},
abstract = {LLNL has developed a low latency, real-time, closed-loop, woofer-tweeter Adaptive Optics Control (AOC) system with a feedback control update rate of greater than 16 kHz. The Low-Latency Adaptive Mirror System (LLAMAS) is based on controller software previously developed for the successful Gemini Planet Imager (GPI) instrument which had an update rate of 1 kHz. By tuning the COTS operating system, tuning and upgrading the processing hardware, and adapting existing software, we have the computing power to implement a Linear-Quadratic-Gaussian (LQG) Controller in real time. The implementation of the LQG leverages hardware optimizations developed for low latency computing and the video game industry, such as fused multiply add accelerators and optimized Fast Fourier Transforms. We used the Intel Math Kernel Library (MKL) to implement the high-order LQG controller with a batch mode execution of 576 6x6 matrix multiplies. We will share our progress, lessons learned and our plans to further optimize performance by tuning high order LQG parameters.},
}