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Record W2087599689 · doi:10.1002/rnc.1233

Feedback control with signal transmission after‐effects

2007· article· en· W2087599689 on OpenAlexaff
Huijun Gao, James Lam, Tongwen Chen, Changhong Wang

Bibliographic record

VenueInternational Journal of Robust and Nonlinear Control · 2007
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsControl theory (sociology)Transmission (telecommunications)Controller (irrigation)ActuatorSIGNAL (programming language)Computer scienceControl (management)Control signalControl engineeringEngineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract In many practical systems, the physical plant, controller, sensor, and actuator are difficult to be located at the same place, and thus signals are required to be transmitted from one place to another. One immediate problem arising from such situations is that signals may exhibit after‐effect phenomena during their transmission. In this paper, we present a new model to characterize the state‐feedback control systems with signal transmission after‐effects, which deals with the transmission after‐effects from sensor to controller and from controller to actuator separately. Analysis and synthesis results based on this new model are established by using a Lyapunov–Krasovskii approach. Numerical simulations are provided to illustrate the usefulness of the theoretical results. Copyright © 2007 John Wiley & Sons, Ltd.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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Same venueInternational Journal of Robust and Nonlinear ControlSame topicStability and Control of Uncertain SystemsFrench-language works237,207