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.
Joyce Fang and Dmitry Savransky, "Model-based estimation and control for off-axis parabolic mirror alignment," Proc. SPIE 10539, Photonic Instrumentation Engineering V, 105390X (Presented at SPIE OPTO: February 01, 2018; Published: 22 February 2018); https://doi.org/10.1117/12.2288775.
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