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Record W2120093255 · doi:10.1109/tia.2015.2455025

Real-Time Testing of a Fuzzy-Logic-Controller-Based Grid-Connected Photovoltaic Inverter System

2015· article· en· W2120093255 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2015
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsLakehead University
FundersKementerian Sains, Teknologi dan Inovasi
KeywordsPhotovoltaic systemInverterFuzzy logicGridComputer scienceGrid-connected photovoltaic power systemProgrammable logic controllerController (irrigation)Control engineeringMaximum power point trackingControl theory (sociology)EngineeringElectrical engineeringControl (management)VoltageArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper presents a novel fuzzy-logic-based high-performance control of a three-phase photovoltaic grid-connected inverter. With the aid of the inverter model and fuzzy-logic-based voltage and current-control schemes, a digital signal processor controller board DS1104 generates the sinusoidal pulsewidth modulated signals for the inverter operation in both stand-alone and grid-connected modes. An inverter prototype was built to verify the effectiveness of the control algorithm. The system demonstrates stable ac output voltage satisfactorily during both transient and steady state with grid and load disturbances. The control system generates 2.48% and 4.64% voltage and current total harmonic distortions, respectively. The output waveforms such as output voltage, injected current, and the system power flow are presented to validate the effectiveness of the control strategy.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.039
GPT teacher head0.260
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