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Record W2022746453 · doi:10.1109/tcst.2014.2364124

Finite-Time Attitude Tracking of Spacecraft With Fault-Tolerant Capability

2014· article· en· W2022746453 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia University
FundersProgram for New Century Excellent Talents in UniversityNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaHeilongjiang Youth Development Foundation
KeywordsControl theory (sociology)SpacecraftFault toleranceInertiaActuatorConvergence (economics)Attitude controlController (irrigation)Tracking (education)Computer scienceControl engineeringFault (geology)Control (management)EngineeringDistributed computingAerospace engineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

A finite-time attitude tracking control scheme is presented for rigid spacecraft subject to constant but unknown inertia and external disturbances. The controller, developed using sliding mode control technique, has great fault-tolerant capability to accommodate four types of actuator faults. Different from most of the existing works on attitude fault-tolerant control (FTC), the developed controller guarantees the desired attitude to be followed in finite time, which is critical for FTC systems. Moreover, the convergence time is an explicit parameter for designer's choice. Thus, the controller design simply meets the finite-time requirement. The attitude-tracking performance is evaluated through a numerical example.

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 categoriesMeta-epidemiology (narrow)
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 score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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