MétaCan
Menu
Back to cohort
Record W2086918515 · doi:10.1109/cdc.2012.6426091

Local full-state observers on linear Lie groups with linear error dynamics

2012· article· en· W2086918515 on OpenAlex
Mikhail Koldychev, Christopher Nielsen

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsObserver (physics)Lie groupMathematicsExponential stabilityInvariant (physics)Linear systemLie algebraDynamics (music)Control theory (sociology)Lie theoryDifferential equationExponential functionLinear differential equationApplied mathematicsComputer scienceMathematical analysisNonlinear systemPure mathematicsArtificial intelligenceControl (management)Physics

Abstract

fetched live from OpenAlex

This paper proposes two local exponential observers for left-invariant systems on linear Lie groups, where the full state of the system is available for measurement. We show that, depending on the observer chosen, local exponential stability of one of the two estimation error dynamics, left or right invariant error dynamics, is obtained. Our proposed observers are noteworthy because their estimation error dynamics are differentially equivalent to a linear and stable differential equation on the Lie algebra. We illustrate our observer designs for an attitude estimation problem on the special orthogonal group SO(3).

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)0.000
metaresearch head score (Gemma)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.013
GPT teacher head0.217
Teacher spread0.205 · 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

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicInertial Sensor and NavigationFrench-language works237,207