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Record W2097322344 · doi:10.1109/icma.2005.1626749

Controller design using white box and black box methods for a magnetically suspended robotic system

2006· article· en· W2097322344 on OpenAlexaff
Mir Behrad Khamesee, David Craig

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMagnetic Bearings and Levitation Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMagnetic levitationControl theory (sociology)Black boxController (irrigation)ElectromagnetWhite boxLevitationComputer scienceControl engineeringPosition (finance)Motion controlTransfer functionControl systemMagnetEngineeringRobotArtificial intelligenceControl (management)Mechanical engineering

Abstract

fetched live from OpenAlex

Formulating vertical position control algorithms for magnetically levitated motion is a difficult task. One of the major problems inherent in identifying the dynamic model is that it is unstable for open-loop control, making it difficult to properly estimate the system dynamics. One proposed method for handling this problem is to first develop a simplified white box model based on magnetic levitation with one electromagnet. A simple controller can then be designed and experimental measurements can be obtained. Black box methods can then be used on the experimental data to estimate the closed loop transfer function, from which it is possible to extract the actual dynamic model of the system. This second model can then be used in order to derive a better control system or used as a component of a state-space model for generalized three-dimensional motion.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.287
Threshold uncertainty score0.637

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 head0.020
GPT teacher head0.265
Teacher spread0.245 · 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
GenreMethods

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

Citations2
Published2006
Admission routes1
Has abstractyes

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