MétaCan
Menu
Back to cohort
Record W2145599560 · doi:10.1177/1077546311426169

A sliding mode vibration controller for lead screw drives

2012· article· en· W2145599560 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 Vibration and Control · 2012
Typearticle
Languageen
FieldEngineering
TopicIterative Learning Control Systems
Canadian institutionsSimon Fraser UniversityMaple Leaf FoodsUniversity of Waterloo
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)VibrationTorqueAngular velocitySliding mode controlMode (computer interface)EngineeringComputer sciencePhysicsNonlinear systemAcousticsControl (management)Classical mechanics

Abstract

fetched live from OpenAlex

The conversion of rotary to translational motion in lead screw drives occurs at the meshing lead screw and nut threads. Adecreasing coefficient of friction with sliding velocity, may lead to instabilities in these drives. In this paper, a sliding mode controller is designed for a two degrees of freedom lead screw drive model. This controller has two objectives: to regulate the lead screw angular velocity to a preset value and to attenuate friction-induced vibrations. Only upper and/or lower bounds of system parameters are assumed to be known. In addition, in the development of the controller no specific model is assumed for the dependence of the coefficient of friction on the relative sliding velocity. Two modifications are applied to the basic discontinuous sliding mode controller to eliminate the inherent chattering problem and to limit thecontrolled input torque levels. Numerical simulation results are presented that show the applicability and the performance 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 score0.954
Threshold uncertainty score0.440

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 communication0.0000.001
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 head0.010
GPT teacher head0.241
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