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Record W2165263296 · doi:10.1109/ecce.2011.6064109

A frequency adaptive resonant controller for fixed point digital implementation at high sampling frequency

2011· article· en· W2165263296 on OpenAlexaff
S. Ali Khajehoddin, Masoud Karimi-Ghartemani, Praveen Jain, Alireza Bakhshai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsRobustness (evolution)Control theory (sociology)Frequency domainComputer sciencePhase-locked loopOpen-loop controllerController (irrigation)Digital controlAutomatic frequency controlSampling (signal processing)Transfer functionElectronic engineeringControl engineeringEngineeringClosed loopJitterControl (management)Electrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

For applications with high sampling frequency and word length limitation, this paper presents a robust resonant (R) controller. The proposed R controller is derived by transforming the representation of conventional R controller to the polar coordinates. The transformed equations entail trigonometric operations similar to a phase-locked loop (PLL) system which results in another inherent advantage of such systems which is frequency adaptiveness. Feasibility and robustness of the proposed controller is illustrated by comparing its performance with a delta-domain implementation of the conventional R controller, which is conventionally used for high sampling frequency applications with fixed point calculations. The validity of the proposed controller is verified using a laboratory prototype of a single-phase uninterruptable power supply (UPS) system operating at high switching frequency.

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)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.788

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)0.0010.000

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 head0.026
GPT teacher head0.222
Teacher spread0.196 · 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.

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

Citations3
Published2011
Admission routes1
Has abstractyes

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