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Record W2144871245 · doi:10.1109/tcst.2008.922506

Tracking Control of an Antagonistic Shape Memory Alloy Actuator Pair

2008· article· en· W2144871245 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 · 2008
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSMA*Shape-memory alloyControl theory (sociology)ActuatorNonlinear systemMiniaturizationTorqueController (irrigation)Materials scienceComputer scienceControl engineeringEngineeringControl (management)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Shape memory alloy actuators exhibit significant nonlinearities in their stress-strain-temperature characteristics which makes them difficult to control. This brief presents a control scheme for trajectory tracking using torque control of shape memory alloy (SMA) actuators connected to a rotary load in an antagonistic configuration. Despite possessing interesting properties such as large force to mass ratio, possibility of miniaturization, light weight, and quiet actuation, SMA exhibits undesirable characteristics that should be taken into account when utilizing them as actuators. The undesirable characteristics include hysteresis, nonlinear temperature dependencies, and slow response. By considering the nonlinear behavior and thermal characteristics of SMA, an inversion-based control scheme with time-varying gains is developed in this brief. The proposed controller does not depend on characteristics of SMA wire and only an approximate model is sufficient. The controller performance is further evaluated on an experimental setup.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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