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Record W2131096571 · doi:10.1109/ivs.1994.639555

A SPICE based fuzzy logic speed controller for PMDC motor drives

2005· article· en· W2131096571 on OpenAlexaff
Ali I. Maswood, A.Μ. Sharaf

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFuzzy Logic and Control Systems
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOmegaControl theory (sociology)Electronic speed controlFuzzy logicPhase planeController (irrigation)SpiceFuzzy control systemPhysicsMathematicsComputer scienceEngineeringArtificial intelligenceElectronic engineeringElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents a novel fuzzy logic rule based speed regulator and its SPICE model for permanent magnet variable speed (PMDC) motor drives. The motor speed is regulated using the speed error excursion vector R~/sub /spl omega// and a proportional plus integral control law. The controller gain is adjusted online using the fuzzy assignment table based on the error excursion vector and its rate of change at any given time, so the control action is scaled online by the error level for the control correction needed. The scaling is based on the excursion error vector R~/sub /spl omega//=/spl radic/(e/sub /spl omega///sup 2/+e/spl dot//sub /spl omega///sup 2/) and its rate of change dR~/sub /spl omega// in the [e/sub /spl omega//-e/spl dot//sub /spl omega//] equivalent phase portrait plane.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.565

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 science0.0010.000
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 head0.019
GPT teacher head0.239
Teacher spread0.221 · 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 designTheoretical or conceptual
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

Citations4
Published2005
Admission routes1
Has abstractyes

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