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Record W2000777285 · doi:10.1109/tac.2012.2218671

Geometric Criteria for the Quasi-Linearization of the Equations of Motion of Mechanical Systems

2012· article· en· W2000777285 on OpenAlexaff
Dong Eui Chang, R. G. McLenaghan

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2012
Typearticle
Languageen
FieldEngineering
TopicControl and Stability of Dynamical Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMathematicsScalar curvatureMathematical analysisTangent bundleRiemannian manifoldLinearizationConstant curvaturePointwiseRiemannian geometryManifold (fluid mechanics)Ricci curvatureFundamental theorem of Riemannian geometryTangent spaceCurvatureNonlinear systemGeometryPhysics

Abstract

fetched live from OpenAlex

A linear transformation of velocity for a mechanical system is said to quasi-linearize the equations of motion of the system if it eliminates all terms quadratic in the velocity. It is well-known that controller/observer synthesis becomes tractable when the dynamics of a mechanical system are in quasi-linearized form. In this technical note, we show that the quasi-linearization property is equivalent to the property that the Lie algebra of Killing vector fields is pointwise equal to the tangent space to the configuration manifold with the Riemannian metric induced by the mass tensor of the mechanical system. A sufficient condition for this property is that the Riemannian manifold be locally symmetric. We further show that a necessary and sufficient condition for quasi-linearizability on 2-D Riemannian manifolds is that the scalar curvature is constant. The above results extend the zero Riemannian curvature condition that has been extensively applied since its introduction in 1992. Moreover, the local symmetricity condition and the constant scalar curvature condition can be easily verified using differentiation.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.018
GPT teacher head0.241
Teacher spread0.222 · 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 designTheoretical or conceptual
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

Citations10
Published2012
Admission routes1
Has abstractyes

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