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Record W187269665

Attitude control of spacecraft using space manipulators

2007· article· en· W187269665 on OpenAlexaff
Krishna Dev Kumar, Godard, Bo Tan

Bibliographic record

VenueInternational Conference on Control Applications · 2007
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSpacecraftControl theory (sociology)Feedback linearizationAttitude controlLinearizationNonlinear systemOrbit (dynamics)Linear-quadratic regulatorOscillation (cell signaling)Optimal controlComputer sciencePhysicsEngineeringControl engineeringControl (management)Aerospace engineeringMathematics
DOInot available

Abstract

fetched live from OpenAlex

Application of linear and nonlinear control methodologies for studying the nonlinear dynamics of a spacecraft with an attached rigid link is demonstrated. Three control laws; based on linear PD control, linear quadratic control, and feedback linearization technique, are incorporated to the system dynamics. The performances of the proposed control methodologies undergoing initial inplane disturbances are compared via numerical simulations. Results indicate that control based on PD and feedback linearization demonstrated similar performances when applied to restore the attitude of the spacecraft. The control techniques were able to stabilize the spacecraft pitch response in less than 0.003 orbits. The attached link although refrains to an oscillating motion due to the presence of gravitational force, its period of oscillation being approximately equal to the period of one orbit. The performance of LQR control indicates that it is possible to stabilize the motion of spacecraft pitch and the rigid link.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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 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

Citations0
Published2007
Admission routes1
Has abstractyes

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