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Record W2086969750 · doi:10.1109/pedg.2014.6878698

Port-Controlled Hamiltonian (PCH)-based control approach for wind energy conversion systems

2014· article· en· W2086969750 on OpenAlexaff
Majid Pahlevani, Shangzhi Pan, Jonathan Mash, Praveen Jain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsControl theory (sociology)Permanent magnet synchronous generatorNonlinear systemComputer scienceWind powerControl engineeringController (irrigation)Hamiltonian (control theory)EngineeringVoltageControl (management)MathematicsPhysics

Abstract

fetched live from OpenAlex

This paper presents a novel control approach to improve the dynamic response of wind energy control systems (WECS) that use a permanent magnet synchronous generator (PMSG) operating under a wide input and load range. In this paper, it's shown that WECS is classified as a Port-Controlled Hamiltonian (PCH) system. Therefore, a nonlinear controller based on PCH is proposed, which is able to robustly control the WECS under parameter uncertainties and disturbances. The performance of the PCH-based controller is evaluated through simulation. Also, the proposed controller is implemented on an experimental prototype. Simulation and experimental results show a robust and fast transient performance compared to the conventional dq-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 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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.168
Teacher spread0.162 · 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 teacher head, not a consensus.

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
Published2014
Admission routes1
Has abstractyes

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