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Record W1877351422 · doi:10.1109/cdc.1989.70231

Towards modeling and control of large space stations

2003· article· en· W1877351422 on OpenAlexaff
N. U. Ahmed, Sang Seok Lim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStability and Controllability of Differential Equations
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOrdinary differential equationSpace (punctuation)Rigid bodyControl theory (sociology)Motion (physics)Boundary (topology)Partial differential equationDifferential equationLyapunov functionComputer scienceCoupling (piping)Equations of motionStability (learning theory)Exponential stabilityMathematicsApplied mathematicsMathematical analysisControl (management)PhysicsClassical mechanicsEngineeringArtificial intelligenceNonlinear system

Abstract

fetched live from OpenAlex

A preliminary formulation is presented for a large space structure. The system consists of a (rigid) massive body, which can play the role of experimental modules located at the center of the space station, and flexible configurations, consisting of several beams, that form the space structure. A complete dynamics of the system has been developed using Hamilton's principle. The equations that govern the motion of the complete system consist of several partial differential equations with boundary conditions describing the vibration of flexible components coupled with six ordinary differential equations that describe the rotational and translational motion of the central body. Consideration is given to the problem of feedback stabilization of the system. Asymptotic stability is proved using Lyapunov's method. This study is expected to provide some insight into the complexity of modeling, analysis, and stabilization of actual space stations. Some numerical results are presented to illustrate the coupling effects and the effectiveness of the suggested feedback controls for stabilization.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.226

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 head0.011
GPT teacher head0.227
Teacher spread0.215 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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