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Record W2008704657 · doi:10.1155/2012/498590

A Memory-Based Hysteresis Model in Piezoelectric Actuators

2012· article· en· W2008704657 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Control Science and Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsDalhousie University
FundersGovernment of Shandong ProvinceNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsHysteresisNonlinear systemControl theory (sociology)Saturation (graph theory)ActuatorPoint (geometry)Nonlinear modelPiezoelectricityMathematicsComputer sciencePhysicsControl (management)AcousticsGeometryArtificial intelligenceCondensed matter physics

Abstract

fetched live from OpenAlex

A mathematical memory-based model is proposed to capture the hysteresis behavior in piezoelectric actuators. It is observed that the ascending (descending) hysteresis curves are alike and converge to one point without memory saturation. Therefore, two, dominant curves are determined and expressed as continuous functions, and the other hysteresis curves are modeled using two dominant curves through nonlinear transforming of coordinate axis. In the event of memory saturation, a new converging point is used to compensate the model prediction error. The experimental study has been carried out and our proposed model prediction method is compared with PI model and the linear model. It shows that the proposed model prediction method is better than other two methods.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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