MétaCan
Menu
Back to cohort
Record W1991976390 · doi:10.1109/tac.2006.876945

Manufacturing Systems: LMI Approach

2006· article· en· W1991976390 on OpenAlexaff
E.K. Boukas

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsControl theory (sociology)Controller (irrigation)Simple (philosophy)State (computer science)Set (abstract data type)Control (management)Computer scienceLinear matrix inequalityMathematical optimizationProduction (economics)MathematicsControl engineeringEngineeringAlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

This note deals with the control of production systems that produce many part types with limited capacity. First, a simple model is used to show that the inventory control problem can be solved using modern control theory. A state feedback controller that forces the cumulative production of the system to track precisely the cumulative demand is proposed. The tracking problem is formulated as an H/sub /spl infin// control problem and the synthesis of the gains of the state feedback controller that guarantees the H/sub /spl infin// tracking performance of the equivalent dynamics is done by solving a given set of linear matrix inequalities (LMIs). A numerical example is provided to show the effectiveness of the developed results. The simple model is then extended to include real facts like inspection and processing times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.004

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Automatic ControlSame topicAdvanced Control Systems OptimizationFrench-language works237,207