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Record W2995705678 · doi:10.1109/iecon.2019.8927171

Design of Pulse Width Modulator based Sliding-Mode Control (SMC-PWM) for Sensor-less Single-Phase Packed U-Cell Inverter

2019· article· en· W2995705678 on OpenAlexaff
Fadia Sebaaly, Hani Vahedi, Hadi Y. Kanaan, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsPulse-width modulationControl theory (sociology)InterfacingRobustness (evolution)Sliding mode controlCapacitorInverterVoltageComputer scienceEngineeringElectronic engineeringElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

In this paper a fixed-switching frequency Pulse width modulator (PWM) based-Sliding Mode Control (SMC) is proposed and applied to a single phase/Five-Level/Sensor-less Packed U-Cell (PUC5) interfacing the utility. The new design takes the advantage of chattering compensation when Gao's reaching law is adopted. SMC-based controller takes in action of maintaining the utility current at a desired reference value with unity power factor and fixed-switching frequency operation. Due to self-voltage balancing feature of PUC5 inverter, auxiliary DC capacitor voltage is regulated through redundant switching states while no sensor, neither regulator are needed. The overall SMC-PWM proposed controller is less complex, more robust towards external disturbances making it suitable for single-phase renewable energy systems interfacing the utility. Simulation results on MATLAB/Simulink are provided to confirm the effectiveness and robustness of the proposed 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: none
GenreCandidate signal: Methods · Consensus signal: Methods
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 science0.0010.000
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 head0.019
GPT teacher head0.230
Teacher spread0.211 · 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
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

Citations7
Published2019
Admission routes1
Has abstractyes

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