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Record W2142135702 · doi:10.1109/icinfa.2011.5948955

Position domain PD control: Stability and comparison

2011· article· en· W2142135702 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIterative Learning Control Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPosition (finance)Control theory (sociology)Domain (mathematical analysis)Motion controlMotion (physics)Computer scienceTracking (education)Time domainStability (learning theory)Frequency domainArtificial intelligenceMathematicsComputer visionControl (management)RobotMathematical analysis

Abstract

fetched live from OpenAlex

In this paper, a position domain PD control for contour tracking is proposed to improve the contour tracking performance. To develop the position domain control, one motion is selected as a master (reference) motion and all other motions are viewed as slave motions. The reference motion is sampled equidistantly in the position domain and used as an independent variable. A dynamic model for the slave motions is developed in the position domain by transforming the original system dynamic equations from the time domain to the position domain. After that, a position domain PD control is proposed, and the stability analysis is conducted based on the Lyapunov function method. The developed position control is applied to linear motion tracking and circular motion tracking, and the comparison study is conducted. Simulation results demonstrate the effectiveness of the position PD control compared with traditional PD control and the crossed-coupled control.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.298

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 head0.016
GPT teacher head0.207
Teacher spread0.191 · 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

Quick stats

Citations12
Published2011
Admission routes2
Has abstractyes

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