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Record W2168184890 · doi:10.1109/acc.2007.4282721

Nonlinear Position Control of Antagonistic Shape Memory Alloy Actuators

2007· article· en· W2168184890 on OpenAlexafffund
V.A. Tabrizi, Mehrdad Moallem

Bibliographic record

VenueProceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)SMA*ActuatorShape-memory alloyController (irrigation)TorqueNonlinear systemPosition (finance)Feedback linearizationComputer scienceControl engineeringEngineeringControl (management)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a control scheme for angular position control of a rotary load using shape memory alloy (SMA) actuators in an antagonistic configuration. Hysteresis and significant nonlinearities in the stress-strain-temperature characteristics hinder effective utilization of SMA actuator. By considering the nonlinear behavior and thermal characteristics of SMA, a force control scheme based on partial feedback linearization and sliding surfaces is developed in this paper to regulate the torque applied by a differential SMA actuator pair. A position controller is then used to generate a desired torque which serves as a reference input for the force tracking controller. The controller is based on sliding surfaces and does not depend on characteristics of SMA. Thus an approximate model of SMA characteristics is sufficient. Experimental studies indicate that the proposed controller performs well in terms of achieving small tracking errors.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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

Citations18
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the ... American Control Conference/Proceedings of the American Control ConferenceSame topicShape Memory Alloy TransformationsFrench-language works237,207