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Record W2166897946 · doi:10.1109/acc.2007.4282812

On the Model-Based Approach to Nonlinear Networked Control Systems

2007· article· en· W2166897946 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings of the ... American Control Conference/Proceedings of the American Control Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)Nonlinear systemComputer scienceNetwork packetFeed forwardInterval (graph theory)Stability (learning theory)Protocol (science)Transfer (computing)Nonlinear modelTelecommunications networkControl (management)Control engineeringMathematicsEngineeringArtificial intelligenceComputer network

Abstract

fetched live from OpenAlex

The problem of model-based stabilization of a nonlinear system based on its approximate discrete-time model is addressed under the assumption that both the feedforward and the feedback paths are subject to network induced constraints. These constraints include irregularity of the transfer intervals, time-varying communication delays, and possibility of packet losses. A communication protocol that copes with these constraints is proposed. "Stability+performance recovery" result for the nonlinear model-based NCS is presented. Simulation results demonstrate that the proposed method improves the maximum allowable transfer interval.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
Consensus categoriesMeta-epidemiology (narrow)
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 score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.003
Science and technology studies0.0010.003
Scholarly communication0.0010.000
Open science0.0060.000
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 head0.014
GPT teacher head0.214
Teacher spread0.201 · 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