Zernike based wavefront alignment in a deployable optic control test bed
Bibliographic record
Abstract
An automated optical alignment method is necessary for the efficient operation of deployable optic-equipped earth observation micro-satellites. Implementation of a linear output feedback controller for the alignment of an active optic is investigated on the Control Test Bed (CTB). The output feedback controller calculates the required positional adjustments of the optic using a multi-variable output measurement. The CTB is a refractive optical system by which the wavefront of an incoming collimated beam is modified by control inputs that adjust the position of a lens. The position of this lens can be translated in the x, y, and z axes (despace and defocus) and rotated about the x and y axes (tip and tilt). In the CTB, a Shack-Hartmann wavefront sensor (SHWFS) measures the output as Zernike coefficients. This setup is intended to emulate the necessary adjustments in a simple deployable optic. We describe the process of developing the output feedback controller that can align the CTB as well as discuss the implications of the scheme to a space-based deployable optic telescope. The aberrations induced by misalignment of the active lens were characterized experimentally by disturbing the system along each degree of freedom about the optically aligned point. The experimental results derive a state observer that can sufficiently estimate the misalignment of the lens from a set of relevant Zernike coefficients. Iterative correction of the estimated misalignment in a closed-loop allowed consistent convergence of the CTB to a nearly flat wavefront.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".