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Record W3010212102 · doi:10.1002/asjc.2277

Finite‐time adaptive fault‐tolerant control for rigid spacecraft attitude tracking

2020· article· en· W3010212102 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

VenueAsian Journal of Control · 2020
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsLakehead University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsControl theory (sociology)Controller (irrigation)Fault toleranceAngular velocityAttitude controlSpacecraftInertial frame of referenceTracking (education)Terminal sliding modeActuatorAdaptive controlTime derivativeUpper and lower boundsStability (learning theory)Computer scienceEngineeringSliding mode controlControl (management)Control engineeringMathematicsNonlinear systemArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Abstract This paper provides a new solution for the finite‐time attitude maneuvers of rigid spacecraft. Uncertainties involving unknown inertial parameters, external disturbances and actuator failures are taken into account. With an effort to achieve attitude tracking despite the impact of uncertainties, a non‐singular terminal sliding mode (NTSM) manifold consisting of attitude errors and angular velocity errors is first constructed. After that, a simple but efficient adaptive updating law is derived to estimate the upper bound of the lumped unknown function in the derivative of sliding surface. Combining NTSM technology and pure adaptive control, a chattering‐free fault‐tolerant controller is presented. The premise assumptions on uncertainties in most of the existing achievements are eliminated, which makes the controller less constrained and more practical. The rigorous proof of finite‐time stability is provided and the convergent regions of tracking errors are explicitly expressed. Finally, numerical simulation is conducted to verify the effectiveness of the proposed control scheme and the comparison experiments with relevant literature demonstrate the satisfactory performances.

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)0.001
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 score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.226
Teacher spread0.208 · 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