Closed-loop control of a 2-D mems micromirror with sidewall electrodes for a laser scanning microscope system
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Bibliographic record
Abstract
This article presents the development and implementation of a robust nonlinear control scheme for a 2-D micromirror-based laser scanning microscope system. The presented control scheme, built around sliding mode control approach and augmented an adaptive algorithm, is proposed to improve the tracking accuracy in presence of cross-axis effect. The closed-loop controlled imaging system is developed through integrating a 2-D micromirror with sidewall electrodes (SW), a laser source, NI field-programmable gate array (FPGA) hardware, the optics, position sensing detector (PSD) and photo detector (PD). The experimental results demonstrated that the proposed scheme is able to achieve accurate tracking of a reference triangular signal. Compared with open-loop control, the scanning performance is significantly improved, and a better 2-D image is obtained using the micromirror with the proposed scheme.
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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 it