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Record W2332732686 · doi:10.2514/6.2009-6289

Coordinated Attitude Control of Spacecraft Formation Without Angular Velocity Feedback: A Decentralized Approach

2009· article· en· W2332732686 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.

Bibliographic record

VenueAIAA Guidance, Navigation, and Control Conference · 2009
Typearticle
Languageen
FieldComputer Science
TopicDistributed Control Multi-Agent Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsSpacecraftAngular velocityAttitude controlControl theory (sociology)Feedback controlControl (management)Computer scienceAerospace engineeringPhysicsControl engineeringEngineeringClassical mechanicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, motivated by recent developments of velocity-free spacecraft (SC) attitude control techniques and behavioral-based SC formation control a decentralized control algorithm for attitude coordination of SC formation without angular velocity feedback is presented. Asymptotic stability of the SC formation is guaranteed by using Lyapunov analysis and LaSalle’s theorem. The advantage of our proposed algorithm is that it requires limited information exchange among the SC in the formation (only attitude information exchange is necessary). Additionally, the proposed algorithm can be extremely useful when angular velocity information of the SC in the formation in not available due to sensor failures or communication constraints. Unlike other popular methods in the robotics area which tend to assume simple dynamics such as linear systems and single or double integrator dynamic models, in this paper, the full nonlinear attitude dynamics of the SC is considered to track fast time-varying reference trajectories.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.936
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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