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Record W2078034148 · doi:10.1260/0263-0923.33.4.455

Model Predictive Control of Vibration in a Two Flexible Link Manipulator — Part I

2014· article· en· W2078034148 on OpenAlexaff
J.R. Elliott, Rickey Dubay, Atef Mohany, Marwan Hassan

Bibliographic record

VenueJournal of low frequency noise, vibration and active control · 2014
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of GuelphOntario Tech UniversityUniversity of New Brunswick
Fundersnot available
KeywordsControl theory (sociology)VibrationVibration controlInertiaModel predictive controlController (irrigation)Computer sciencePayload (computing)ActuatorPlanarPhysicsControl (management)Acoustics

Abstract

fetched live from OpenAlex

A model predictive controller (MPC) in the form of dynamic matrix control (DMC) is implemented for attenuating in-plane vibrations of a two flexible link planar manipulator. The rotation of the joints and inertia effect of both the joints and links induce vibration. Piezoelectric actuators, mounted in a bimorph configuration, provide the control actions to reduce vibrations. Implementation of this control scheme is shown to provide appreciable attenuation of vibration over the uncontrolled case, increasing the damping ratio for the first and second link by a factor of 5.99 and 3.40, respectively. DMC control is further shown to reduce the mean amplitude of dominant vibrations from the uncontrolled case by 90.0% and 87.4%, respectively, for the first and second links. Furthermore, for the two link setup, this control is shown to outperform the more conventional ProportionalIntegral-Derivative (PID) control and is sufficiently robust to handle an unknown payload.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.219
Teacher spread0.211 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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