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Record W4401567685 · doi:10.1109/tie.2024.3429659

A Low-Energy Variable Air Gap-Based Reluctance-Actuated Motion System

2024· article· en· W4401567685 on OpenAlexafffund
Mohammad Al Saaideh, Michael Pumphrey, Natheer Alatawneh, Khaled F. Aljanaideh, Mohammad Al Janaideh

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2024
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsMagnetic reluctanceVariable (mathematics)Control theory (sociology)Air gap (plumbing)Reluctance motorComputer scienceMotion (physics)Energy (signal processing)Control engineeringTorqueEngineeringPhysicsSwitched reluctance motorElectrical engineeringControl (management)Materials scienceArtificial intelligenceMathematicsMagnet

Abstract

fetched live from OpenAlex

This article presents a design and characterization of a motion stage driven by a low-energy reluctance actuator (RA). The low-energy concept reflects the ability of the RA to generate a high force with low current values due to the quadratic relation of the force with the input current. First, the critical voltage is determined for stable operation; then, the open-loop response is obtained under different applied voltages. The experimental results show that the motion stage exhibits nonlinear force characteristics. Second, a feedforward controller is proposed to linearize the dynamic behavior of the RA. The experimental results show the ability of the proposed feedforward controller to achieve linear input-output characteristics between the desired force and the measured force. Next, a state feedback controller based on a robust backstepping approach is designed to achieve the desired displacement, considering the force errors due to the bounded open-loop compensation, which can be reduced by tuning the controller gains. The experimental results show the ability to achieve a tracking to a step reference signal with an error less than 2% and to a sinusoidal reference signal with a tracking error less than 15% of motion range for a moving mass about of 1.6 kg.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.200
Teacher spread0.185 · 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.

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

Citations4
Published2024
Admission routes2
Has abstractyes

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