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Record W2999085032 · doi:10.18280/jesa.520614

Simulation of Model Predictive Controller Based Oscillatory Water Pumping System for Residential Applications

2019· article· en· W2999085032 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering and Technology Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsModel predictive controlControl theory (sociology)Controller (irrigation)Computer scienceControl engineeringEnvironmental scienceEngineeringControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

The utilization of renewable energy sources has been rising from the last few years due to their enormous advantages. This paper presents the design of bladeless wind turbine utilizing the principles of the wind. It involves design of model predictive controller based maximum power point tracking system which tracks the voltage, current and power of the bladeless wind turbine. This paper also involves the design of water pumping system with the utilization of single phase induction motor and so the design of single phase inverter has been proposed. It presents the battery management system which continuously monitors the charging and discharging states of the battery based up on the power requirement. The entire system was designed and the results have been analyzed using MATLAB Simulink.

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 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 score0.809
Threshold uncertainty score0.537

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 science0.0000.000
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 head0.012
GPT teacher head0.230
Teacher spread0.219 · 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