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Record W2015299036 · doi:10.1115/imece2006-15913

Tracking Controller for a Piezoworm™ Stage

2006· article· en· W2015299036 on OpenAlexaff
Shaun P. Salisbury, D. Waechter, Ridha Ben Mrad, S. Eswar Prasad, R. Blacow, Bin Yan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)PID controllerTracking (education)Controller (irrigation)Computer scienceControl engineeringOpen-loop controllerLoop (graph theory)Closed loopEngineeringControl (management)Artificial intelligenceMathematicsTemperature control

Abstract

fetched live from OpenAlex

In this paper, a closed-loop tracking controller is described that expands the application of the piezoworm stage. A dynamic model of the piezoworm is presented complete with a rule-based friction model to accurately capture the clamp behavior. This dynamic model is used to assess different closed loop controllers for tracking performance. It is determined that a PID controller would offer good performance when the motor is subject to step and sinusoidal signals and state feedback control did not lead to improved performance when compared to the PID performance.

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 score0.980
Threshold uncertainty score0.330

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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