MétaCan
Menu
Back to cohort
Record W2029708194 · doi:10.1109/tmech.2011.2128339

A Novel Discrete ARMA-Based Model for Piezoelectric Actuator Hysteresis

2011· article· en· W2029708194 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

VenueIEEE/ASME Transactions on Mechatronics · 2011
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsHysteresisAutoregressive modelAutoregressive–moving-average modelNonlinear systemActuatorPiezoelectricityControl theory (sociology)Identification (biology)Computer scienceNonlinear modelMathematicsPhysicsControl (management)EconometricsAcousticsArtificial intelligence

Abstract

fetched live from OpenAlex

Hysteresis is an important nonlinear effect exhibited by piezoelectric actuators (PEAs) and its modeling has been drawing considerable attention. This paper presents the development of a novel discrete model based on the concept of autoregressive moving average for the PEA hysteresis, and its parameter identification method as well. Experiments were carried out to verify the effectiveness of the developed model. The result obtained shows that the developed model can well represent the PEA hysteresis, with improved performance over an existing discrete hysteresis model.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.025
GPT teacher head0.213
Teacher spread0.187 · 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