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Record W2329882697 · doi:10.3934/jgm.2010.2.397

Geometric Jacobian linearization and LQR theory

2010· article· en· W2329882697 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of Geometric Mechanics · 2010
Typearticle
Languageen
FieldEngineering
TopicControl and Dynamics of Mobile Robots
Canadian institutionsQueen's University
FundersGovernment of Ontario
KeywordsControllabilityMathematicsLinearizationJacobian matrix and determinantLyapunov functionAffine transformationFeedback linearizationControl theory (sociology)Tangent spaceTangentTrajectoryLinear systemApplied mathematicsNonlinear systemMathematical analysisComputer sciencePure mathematicsGeometryControl (management)

Abstract

fetched live from OpenAlex

The procedure of linearizing a control-affine system along a non-trivialreference trajectory is studied from a differential geometric perspective. Acoordinate-invariant setting for linearization is presented. With thelinearization in hand, the controllability of the geometric linearization ischaracterized using an alternative version of the usual controllability testfor time-varying linear systems. The various types of stability are definedusing a metric on the fibers along the reference trajectory and Lyapunov'ssecond method is recast for linear vector fields on tangent bundles. Withthe necessary background stated in a geometric framework, linear quadraticregulator theory is understood from the perspective of the Maximum Principle.Finally, the resulting feedback from solving the infinite time optimalcontrol problem is shown to uniformly asymptotically stabilize thelinearization using Lyapunov's second method.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.182
Teacher spread0.178 · 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