MétaCan
Menu
Back to cohort
Record W2167614357 · doi:10.1109/87.896741

Passivity-based stability and control of hysteresis in smart actuators

2001· article· en· W2167614357 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 Transactions on Control Systems Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPassivityActuatorHysteresisControl theory (sociology)Controller (irrigation)Smart materialShape-memory alloyNonlinear systemControl engineeringNoise (video)Stability (learning theory)Computer scienceRepresentation (politics)EngineeringControl (management)Materials sciencePhysicsArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

The past decade has seen an increase in the use of smart materials in actuator design, notably for inclusion in active structures such as noise-reducing paneling or vibration-controlled buildings. Materials such as shape memory alloys (SMAs), piezoceramics, magnetostrictives and others all offer exciting new actuation possibilities. However, all of these materials present an interesting control challenge due to their nonlinear hysteretic behavior in some regimes. We look at the energy properties of the Preisach hysteresis model, widely regarded as the most general hysteresis model available for the representation of classes of hysteretic systems. We consider the ideas of energy storage and minimum energy states of the Preisach model, and derive a passivity property of the model. Passivity is useful in controller design, and experimental results are included showing control of a differential shape memory alloy actuator using a passivity-based rate controller.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.186
Teacher spread0.180 · 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