MétaCan
Menu
Back to cohort
Record W3096232780 · doi:10.18280/ejee.224-502

Decentralized T-S Fuzzy Control for Solar PV Powered Water Pumping System Driving by Induction Motor

2020· article· en· W3096232780 on OpenAlexvenueno aff
Zeineb Ben Safia, Moez Allouch, Mohamed Chaabane

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2020
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)Photovoltaic systemMaximum power point trackingMaximum power principleInduction motorController (irrigation)Water pumpingDC motorPower (physics)InverterFuzzy logicComputer scienceEngineeringControl engineeringVoltageControl (management)PhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a decentralized Takagi Sugeno (T-S) control scheme for a PV powered water pumping system, which is composed of a photovoltaic generator (PVG) supplying via a DC-DC boost converter, a DC-AC inverter, an Induction Motor coupled to a centrifugal pump. A T-S fuzzy controller is developed for MPPT (Maximum Power Point Tracking) to control the DC-DC boost converter, under variable solar irradiation and ambient temperature. An observer-based T-S fuzzy controller is dedicated to control the IM to guarantee the field-oriented control performances. From the optimal PV power provided in the MPP conditions, the optimal speed is calculated and delivered to control the IM, so that the proposed PV pumping system operates in optimal conditions and thus, maximizes the quantity of water pumped daily. Finally, simulation results are presented for both transient and steady state operation while taking into account all changes in climatic conditions, in order to validate the efficiency of the developed decentralized controller.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.189
Teacher spread0.181 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Electrical EngineeringSame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207