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Record W2744262249 · doi:10.1177/0954407017704780

Decoupled disturbance rejection control for a turbocharged engine with a dual-loop exhaust gas recirculation system

2017· article· en· W2744262249 on OpenAlexafffund
Song Chen, Fengjun Yan

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Body orificeExhaust manifoldRobustness (evolution)State observerInternal modelInlet manifoldTurbochargerControl systemComputer scienceEngineeringNonlinear systemInternal combustion engineAutomotive engineeringPhysicsControl (management)Gas compressor

Abstract

fetched live from OpenAlex

Dual-loop exhaust gas recirculation with a variable-geometry turbocharger is an effective architecture for achieving desired intake manifold conditions, such as the temperature, the pressure and the oxygen concentration of the intake manifold, which have critical roles in advanced combustion mode control. However, the widely used control-oriented model is derived on the basis that the heat transfer between the pipes and the gas is negligible, which means that it suffers from non-trivial errors. Simulation results show that other error sources, including the volumetric efficiency and the orifice equation, are difficult to calibrate accurately and also cause significant errors in the system, particularly in transient situations. Modified active disturbance rejection control with an extended state observer is utilized to deal with the non-linear, multiple-input multiple-output system in this paper. It is demonstrated that the performance of active disturbance rejection control mainly depends on the performance of the extended state observer. In this paper, an extended state observer, which is based on the sliding-mode concept rather than the conventional linear observer, is introduced. By taking advantage of its strong robustness, the system is decoupled into three loops. For each loop, the internal errors and the external errors, including the modelling error and the coupling effects, are lumped into one term; they are then actively estimated and cancelled out by the control input in real time. The proposed method was validated using calibrated GT-Power model simulations.

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)0.003
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 score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.219
Teacher spread0.209 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile EngineeringSame topicAdvanced Combustion Engine TechnologiesFrench-language works237,207