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High-bandwidth image-based predictive laser stabilization via optimized Fourier filters.

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    |January 11, 2023
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    Summary

    A new predictive feed-forward algorithm stabilizes kHz laser pulse trains against vibrations up to 400 Hz. This method uses optimized Fourier filters and machine learning for precise control, outperforming traditional PID controllers.

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    Area of Science:

    • Optics and Photonics
    • Control Systems Engineering
    • Laser Physics

    Background:

    • kHz-class pulsed lasers are crucial for applications like laser-plasma acceleration and precision manufacturing.
    • External factors such as vibrations and environmental changes cause transverse position fluctuations in laser pulse trains.
    • Traditional PID controllers have limited effectiveness in suppressing vibrations at frequencies relevant to these laser systems.

    Purpose of the Study:

    • To develop an advanced control algorithm for stabilizing the transverse position of kHz laser pulse trains.
    • To enhance the stabilization bandwidth beyond the limitations of conventional PID controllers.
    • To implement a cost-effective system using off-the-shelf components and machine learning.

    Main Methods:

    • A predictive feed-forward algorithm employing optimized Fourier filters for online identification and filtering of discrete disturbance frequencies.
    • Integration of off-the-shelf CMOS cameras and piezo-electric actuated mirrors connected to a standard PC.
    • Development of a machine-learning-based model to compensate for piezo mirror dynamics, including hysteresis.

    Main Results:

    • The predictive feed-forward algorithm significantly enhanced the stabilization bandwidth, reaching up to the Nyquist limit.
    • Externally induced vibrations up to 400 Hz were attenuated by a factor of five on a 1 kHz laser pulse train.
    • The system demonstrated superior performance compared to standard PID control schemes in vibration suppression.

    Conclusions:

    • The presented predictive feed-forward algorithm offers a robust and effective solution for stabilizing kHz laser pulse trains against vibrations.
    • The use of machine learning and off-the-shelf components makes this high-precision laser control system accessible and cost-effective.
    • This technology has broad implications for advancing industrial and scientific applications requiring precise laser delivery.