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Record W4409321150 · doi:10.1002/asjc.3666

Sampled‐data enhanced extended state observer‐based dynamic event‐triggered tracking control for perturbed networked systems

2025· article· en· W4409321150 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.

Bibliographic record

VenueAsian Journal of Control · 2025
Typearticle
Languageen
FieldEngineering
TopicStability and Control of Uncertain Systems
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsControl theory (sociology)Computer scienceObserver (physics)State observerTracking (education)State (computer science)Control (management)Control systemControl engineeringEngineeringArtificial intelligenceNonlinear systemPhysicsAlgorithmPsychology

Abstract

fetched live from OpenAlex

Abstract This paper aims for precise tracking with disturbance rejection and low energy consumption. An event‐triggered controller based on a sampled‐data enhanced extended state observer (SD‐EESO) is designed for a networked tracking system. In this method, the measured output and the given signal are sampled and transmitted to an observer, which is designed to periodically estimate the negative disturbance and tracking errors. Furthermore, a dynamic event‐triggered state feedback–feedforward controller is developed. It is shown that as long as the sampling period satisfies the given condition, the estimation error and the tracking error are both globally bounded stable. The numerical simulation and the direct current (DC) brush motor position control example show the superiority of the designed control scheme.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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