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Record W1971282418 · doi:10.2514/1.52287

Vibration Control Using Input Shaping and Adaptive Positive Position Feedback

2011· article· en· W1971282418 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

VenueJournal of Guidance Control and Dynamics · 2011
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsYork University
Fundersnot available
KeywordsControl theory (sociology)VibrationController (irrigation)Position (finance)Computer scienceAdaptive controlActuatorInput shapingEstimatorVibration controlActive vibration controlFeed forwardControl engineeringEngineeringControl (management)MathematicsArtificial intelligencePhysicsAcoustics

Abstract

fetched live from OpenAlex

DOI: 10.2514/1.52287 This paper presents a vibration control strategy for a flexible manipulator with a collocated piezoelectric sensor/ actuator pair. Dynamic modeling of the flexible manipulator is first shown, and then a control law is developed. The proposed vibration controller combines the input shaping technique with multimode adaptive positive position feedback. An adaptive parameter estimator based on the recursive least-square method is developed to update the system’s natural frequencies, which are used by the adaptive positive position feedback. A proportional-derivative controller is combined with the proposed vibration controller to suppress vibration while slewing the manipulator. Simulation results are presented to illustrate the efficacy of the proposed 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 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 score0.816
Threshold uncertainty score0.654

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 head0.013
GPT teacher head0.200
Teacher spread0.187 · 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