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Record W2789496403 · doi:10.2514/1.g003281

Velocity-Free Attitude Stabilization of a Nadir-Pointing Underactuated Rigid Spacecraft

2018· article· en· W2789496403 on OpenAlexafffund
Alexander Frias, Anton de Ruiter, Krishna Dev Kumar

Bibliographic record

VenueJournal of Guidance Control and Dynamics · 2018
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl theory (sociology)UnderactuationSpacecraftAngular velocityObserver (physics)Nonlinear systemSylvester's law of inertiaAttitude controlCircular orbitOrbit (dynamics)InertiaComputer scienceMathematicsPhysicsEngineeringControl (management)Aerospace engineeringSymmetric matrixClassical mechanics

Abstract

fetched live from OpenAlex

This paper examines the velocity-free attitude stabilization of an underactuated nadir-pointing rigid spacecraft in a circular orbit in the presence of time-varying disturbances. A nonlinear observer is used to estimate the angular velocity of the spacecraft to complete an output feedback control law. A sliding-mode control strategy is proposed for this stabilization problem in conjunction with a nonlinear observer. The local ultimate boundedness of the closed-loop system is rigorously proven. Numerical examples demonstrate the performance of the controller in the presence of time-varying disturbances, nonzero orbital eccentricity, inertia matrix uncertainties, and measurement noise in a sampled data implementation. In particular, even though the theoretical ultimate boundedness guarantees are local, the numerical examples demonstrate ultimate boundedness with large initial attitude errors.

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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.733
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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 teacher head, 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

Citations7
Published2018
Admission routes2
Has abstractyes

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