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Model-based estimation and control for off-axis parabolic mirror alignment
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Paper Abstract

This paper propose an model-based estimation and control method for an off-axis parabolic mirror (OAP) alignment. Current studies in automated optical alignment systems typically require additional wavefront sensors. We propose a self-aligning method using only focal plane images captured by the existing camera. Image processing methods and Karhunen-Loève (K-L) decomposition are used to extract measurements for the observer in closed-loop control system. Our system has linear dynamic in state transition, and a nonlinear mapping from the state to the measurement. An iterative extended Kalman filter (IEKF) is shown to accurately predict the unknown states, and nonlinear observability is discussed. Linear-quadratic regulator (LQR) is applied to correct the misalignments. The method is validated experimentally on the optical bench with a commercial OAP. We conduct 100 tests in the experiment to demonstrate the consistency in between runs.

Paper Details

Date Published: 22 February 2018
PDF: 16 pages
Proc. SPIE 10539, Photonic Instrumentation Engineering V, 105390X (22 February 2018); doi: 10.1117/12.2288775
Show Author Affiliations
Joyce Fang, Cornell Univ. (United States)
Dmitry Savransky, Cornell Univ. (United States)


Published in SPIE Proceedings Vol. 10539:
Photonic Instrumentation Engineering V
Yakov G. Soskind, Editor(s)

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