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Singular Perturbation-Based Approach for Robust Control of Reluctance-Actuated Motion Systems

2023· article· en· W4391045191 on OpenAlexaff
Mohammad Al Saaideh, Almuatazbellah Boker, Mohammad Al Janaideh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of GuelphMemorial University of Newfoundland
Fundersnot available
KeywordsFeed forwardControl theory (sociology)Control engineeringComputer scienceMotion controlActuatorControl systemController (irrigation)Perturbation (astronomy)Optimal controlSingular perturbationRobust controlControl (management)EngineeringRobotMathematicsArtificial intelligenceMathematical optimization

Abstract

fetched live from OpenAlex

This paper introduces a new composite control approach for a motion system driven by a reluctance actuator. To achieve high-performance control, the method leverages singular perturbation theory to divide the problem into two components: a fast control problem and a slow control problem. A feedforward controller is developed based on the reduced system to address the fast control problem. The dynamic model is then formulated using the feedforward control law to address the slow control problem. Full-state feedback control chooses the input signal that results in the desired reference signal. The output signal of the feedback control is treated as the desired input for the feedforward controller. With the proposed approach, the feedforward controller for the fast dynamic eliminates the need for measuring the fast states. The effectiveness of the proposed approach is demonstrated through experimental testing.

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: none
Teacher disagreement score0.988
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.196
Teacher spread0.178 · 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
Published2023
Admission routes1
Has abstractyes

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