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Record W1980972935 · doi:10.1002/rnc.1206

Analysis of response of second‐order sliding mode controllers to external inputs in frequency domain

2007· article· en· W1980972935 on OpenAlexaff
Igor Boiko, Ivan Castellanos, Leonid Fridman

Bibliographic record

VenueInternational Journal of Robust and Nonlinear Control · 2007
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFrequency domainControl theory (sociology)Nonlinear systemDescribing functionFrequency responseMode (computer interface)AmplitudeHarmonicFunction (biology)Transfer functionPhase (matter)Sliding mode controlTime domainDomain (mathematical analysis)Computer scienceMathematicsControl (management)EngineeringAcousticsPhysicsMathematical analysisOpticsArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Response of systems with the second‐order sliding‐mode (SOSM) control algorithms to an external harmonic excitation is analysed in the frequency domain. The analysis is done via application of the concept of the equivalent gain of a nonlinear function. The equivalent gain is used as a model of propagation of averaged values of signals through nonlinear elements of the system. Two SOSM algorithms: twisting and super‐twisting are analysed. The results are presented in the format of the conventional amplitude and phase frequency response. 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)0.002
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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

Citations23
Published2007
Admission routes1
Has abstractyes

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