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Run-to-Run Optimization Control Within Exact Inverse Framework for Scan Tracking.

Ivan L Yeoh1, Per G Reinhall2, Martin C Berg2

  • 1Department of Mechanical Engineering, University of Washington, Seattle, WA 98195

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|July 11, 2017
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Summary
This summary is machine-generated.

A new run-to-run optimization controller improves scanning fiber device accuracy by using sparse measurements. This method enhances image quality and adapts to temperature changes for continuous video display.

Keywords:
exact inversionfeedforward controlrun-to-run optimizationscanning fiber endoscope

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Area of Science:

  • Engineering
  • Control Systems
  • Optics

Background:

  • Repetitive processes require precise control for optimal performance.
  • Existing feedback controllers can be complex and parameter-intensive.
  • Scanning fiber devices for imaging demand high accuracy and stability.

Purpose of the Study:

  • To develop a novel run-to-run optimization controller for scanning fiber devices.
  • To improve scan accuracy and adapt to environmental variations like temperature.
  • To maintain high image quality in applications such as scanning fiber endoscopes.

Main Methods:

  • Utilized a run-to-run optimization framework with sparse measurements.
  • Estimated system energy and iteratively updated input parameterizations.
  • Employed a feedforward control structure with exact-inversion.
  • Conducted analysis, simulations, and experimental investigations.

Main Results:

  • Demonstrated improved scan accuracy compared to previous methods.
  • Showcased automatic controller adaptation to changing operating temperatures.
  • Validated performance on a scanning fiber endoscope with quantitative error analysis.
  • Maintained high image quality across a 20°C temperature rise at 56 Hz video.

Conclusions:

  • The new run-to-run controller offers enhanced performance for scanning fiber devices.
  • The controller's adaptability ensures consistent image quality under varying conditions.
  • This approach provides a robust solution for high-fidelity imaging in demanding applications.