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Record W1976702290 · doi:10.1115/imece2007-44117

Vibration Control of a Flexible Link Manipulator Using an Array of Fiber-Optic Curvature Sensors and Piezoelectric Actuators

2007· article· en· W1976702290 on OpenAlexaff
Kerem Gürses, Bradley J. Buckman, Edward J. Park

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsActuatorCurvatureVibrationControl theory (sociology)Vibration controlController (irrigation)Angular velocityPiezoelectric sensorLink (geometry)Computer scienceAcousticsPiezoelectricityEngineeringPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a novel feedback sensing approach for actively suppressing vibrations of a single-link flexible manipulator. Slewing of the flexible link by a rotating hub induces vibrations in the link that persist long after the hub stops rotating. These vibrations are suppressed through a combined scheme of PD-based hub motion control and proposed piezoelectric (PZT) actuator control, which is a composite linear and velocity feedback controller. Lyapunov approach was used to synthesize the controller based on a finite element model of the system. Its realization was possible due to the availability of both linear and angular velocity feedback provided by a unique, commercially-available fiber optic curvature sensor array, called ShapeTape™. It is comprised of an array of fiber optic curvature sensors, laminated on a long, thin ribbon tape, geometrically arranged in such a way that, when it is embedded into the flexible link, the bend and twist of the link’s centerline can be measured. Experimental results show the effectiveness of the proposed approach.

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 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 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 score0.902
Threshold uncertainty score0.452

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 teacher head, 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

Citations1
Published2007
Admission routes1
Has abstractyes

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