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Record W2294751495 · doi:10.1080/15599612.2015.1095956

Closed-loop control of a 2-D mems micromirror with sidewall electrodes for a laser scanning microscope system

2015· article· en· W2294751495 on OpenAlexafffund
Hui Chen, Albert Chen, Wei Sun, Zhen Sun, John T. W. Yeow

Bibliographic record

VenueInternational Journal of Optomechatronics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsUniversity of Waterloo
FundersNational Key Research and Development Program of ChinaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsDetectorOpticsField-programmable gate arrayLaserMicroscopeMicroelectromechanical systemsDigital micromirror deviceComputer scienceLaser scanningTracking (education)SIGNAL (programming language)Materials sciencePhysicsComputer hardwareOptoelectronics

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.284
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2015
Admission routes2
Has abstractyes

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