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FUZZY LOGIC BASED POSITION CONTROL OF A PMSM SERVO DRIVE

2007· article· en· W2079784792 on OpenAlexaffvenue
M. Nasir Uddin, T.S. Radwan, M.A. Rahman

Bibliographic record

VenueControl and Intelligent Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsMemorial University of NewfoundlandLakehead University
Fundersnot available
KeywordsControl theory (sociology)Vector controlControl engineeringFuzzy logicServo driveController (irrigation)Position (finance)PID controllerComputer scienceServomechanismElectronic speed controlServo controlServoServomotorDigital signal processorEngineeringDigital signal processingControl (management)Induction motorTemperature controlArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a novel fuzzy position controller (FPC) for an interior type permanent magnet synchronous motor (PMSM). The FPC is employed as an outermost control-loop in a closed-loop vector control scheme of PMSM drive. A synchronous frame proportional-integral (PI) controller is employed as an inner speed control loop. The controllers are designed based on the indirect field oriented control. The control scheme can be used for both position and speed control applications by enabling and disabling the position controller, respectively. The control scheme is implemented using Digital Signal Processor TMS320C31. The performance of the proposed control scheme for a PMSM servo-motor drive is investigated both theoretically and experimentally at different operating conditions. The performance of the proposed FPC is found robust for industrial applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes2
Has abstractyes

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Same venueControl and Intelligent SystemsSame topicSensorless Control of Electric MotorsFrench-language works237,207