High sensitivity accelerometer operating on the border of stability with digital sliding mode control
Why this work is in the frame
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Bibliographic record
Abstract
We propose a novel sliding mode control (SMC), implemented on FPGA, for robust stabilization and high sensitivity operation of a capacitive micro-accelerometer on the pull-in border of stability. SMC feedback enforces a maximum sensitivity position of the proof mass in a normally unstable equilibrium, while the value of the external acceleration is extracted from the “chattering” noise bitstream produced by the controller action. Experimental results show a stabilization of the proof mass at the pull-in position and a measurement of small accelerations. The proposed technique, implemented in LabView and FPGA hardware, represents a promising alternative for the digital control of capacitive MEMS devices, with a lighter implementation footprint than common sigma-delta approaches used for inertial sensors.
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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