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Record W2137054283 · doi:10.1109/cdc.2008.4738651

Cycle adaptive feedforward approach control of an electromagnetic valve actuator

2008· article· en· W2137054283 on OpenAlexaff
Jimmy Tsai, Charles Robert Koch, Mehrdad Saif

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of AlbertaSimon Fraser University
Fundersnot available
KeywordsFeed forwardActuatorSoft landingControl theory (sociology)Controller (irrigation)Adaptive controlNoise (video)EngineeringControl engineeringValve actuatorInternal combustion engineComputer scienceActive noise controlConstant (computer programming)Control (management)Automotive engineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

An electromagnetic valvetrain on an internal combustion engine can improve the engine thermal efficiency but requires control to achieve soft landing and to avoid excessive wear and noise. Since the valves open and close repetitively, cycle adaptive control can be utilized. A cyclic adaptive feedforward approach controller for automotive electromagnetic valve is presented. This method uses a Nelder-Mead direct search algorithm with the goal of setting constant initial conditions for the landing control. Simulation and testbench results are presented and they show that the approach control works well for disturbances that are slow compared to the valve travel time.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.459

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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
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

Citations13
Published2008
Admission routes1
Has abstractyes

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