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Record W2117314070 · doi:10.1002/rnc.1696

Generating oscillations in inertia wheel pendulum via two‐relay controller

2011· article· en· W2117314070 on OpenAlexaff
Luis T. Aguilar, Igor Boiko, Leonid Fridman, Leonid B. Freidovich

Bibliographic record

VenueInternational Journal of Robust and Nonlinear Control · 2011
Typearticle
Languageen
FieldEngineering
TopicControl and Stability of Dynamical Systems
Canadian institutionsUniversity of Calgary
FundersCentro de Investigación y de Estudios Avanzados del Instituto Politécnico NacionalConsejo Nacional de Ciencia y Tecnología
KeywordsControl theory (sociology)RelayInertiaLinearizationPendulumFrequency domainController (irrigation)AmplitudeComputer scienceNonlinear systemMathematicsControl engineeringEngineeringPhysicsMathematical analysisControl (management)Classical mechanics

Abstract

fetched live from OpenAlex

Abstract The problem of generating oscillations of the inertia wheel pendulum is considered. We combine exact feedback linearization with two‐relay controller, tuned using frequency‐domain tools, such as computing the locus of a perturbed relay system. Explicit expressions for the parameters of the controller in terms of the desired frequency and amplitude are derived. Sufficient conditions for orbital asymptotic stability of the closed‐loop system are obtained with the help of the Poincaré map. Performance is validated via experiments. The approach can be easily applied for a minimum phase system, provided the behavior of the states of the zero dynamics is of no concern. Copyright © 2011 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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0010.000
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 head0.013
GPT teacher head0.213
Teacher spread0.199 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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