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Record W2171236883 · doi:10.1109/acc.2008.4586771

A generalized rate dependent play operator for characterizing asymmetric and symmetric hysteresis nonlinearities

2008· article· en· W2171236883 on OpenAlexaff
Mohammad Al Janaideh, Subhash Rakheja, Chun Yi Su

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsConcordia University
FundersMichigan State University
KeywordsHysteresisControl theory (sociology)ActuatorOperator (biology)Displacement (psychology)Function (biology)Describing functionMathematicsNonlinear systemMathematical analysisPhysicsTopology (electrical circuits)Computer scienceCondensed matter physics

Abstract

fetched live from OpenAlex

In this paper, a generalized rate dependent Prandtl-Ishlinskii model is proposed to characterize both the symmetric and asymmetric input-output hysteresis, as a function of the time rate of input. The model is realized upon formulation and integration of a generalized rate dependent play operator capable of generating minor as well as major hysteresis loops with varying slopes of ascending and descending input-output curves. A dynamic threshold function is proposed to enhance the prediction of rate-dependent hysteresis nonlinearities. The validity of the generalized model is demonstrated by comparing its displacement responses with the measured symmetric and asymmetric responses obtained for piezoceramic and magnetostrictive actuators under input frequencies of 50–200 Hz and 10–50 Hz, respectively. The results show the capability of the proposed model to characterize asymmetric and symmetric rate dependent hysteresis nonlinearities in smart actuators

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.202
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations4
Published2008
Admission routes1
Has abstractyes

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