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Record W2076019180 · doi:10.2514/1.59023

Real-Time Nonlinear Attitude Control System for Nanosatellite Applications

2013· article· en· W2076019180 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

VenueJournal of Guidance Control and Dynamics · 2013
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsYork University
Fundersnot available
KeywordsControl theory (sociology)Attitude controlReaction wheelFuzzy logicController (irrigation)Nonlinear systemComputer scienceSliding mode controlControl engineeringControl systemFault toleranceEngineeringControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

This paper develops a fault-tolerant attitude controller for next-generation nanosatellites. The proposed fault-tolerant attitude control algorithms in this study are based on first-order and high-order sliding-mode control theories as well as fuzzy logic systems to achieve low cost and real-time autonomy. A locally asymptotically stable adaptive fuzzy first-order sliding-mode controller is chosen as the best solution to the local attitude control tracking problem. This novel fault-tolerant controller is validated by simulation results with reaction wheel Coulomb friction, saturation, noise, dead zones, bias faults, and external disturbances. Simulation and testing results presented in the paper demonstrate that the attitude control system can provide successful pointing and tracking in the presence of system uncertainties for a specified class of reaction wheel failures.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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