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Record W2898178326 · doi:10.1109/tcst.2018.2875426

Fault-Tolerant Prescribed Performance Attitude Tracking Control for Spacecraft Under Input Saturation

2018· article· en· W2898178326 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

VenueIEEE Transactions on Control Systems Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsUniversity of Victoria
FundersNational Natural Science Foundation of China
KeywordsSpacecraftControl theory (sociology)Tracking (education)Attitude controlFault toleranceSaturation (graph theory)Control (management)Control engineeringComputer scienceEngineeringAerospace engineeringReliability engineeringMathematicsPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

This brief examines the problem of attitude tracking control with prescribed performance guarantees for a spacecraft subjected to actuator faults and input saturation. To pursue this, the open-loop tracking error dynamics with certain designer-specified performance constraints is first transformed into an equivalent “state-constrained” one, via an error transformation; furthermore, the resulting dynamics is augmented with a dynamic system, which is tactfully constructed to ensure that the control input satisfies the magnitude limits. Subsequently, a robust fault-tolerant controller is developed by using a low-pass filter and an auxiliary system in conjunction with adaptive backstepping design. It is shown that the control algorithm developed not only achieves the stable attitude tracking with prescribed behavioral metrics but also guarantees the boundedness of all the closed-loop signals. Finally, simulation results are given to evaluate the efficacy of the proposed scheme.

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 score0.949
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 integrity0.0010.001
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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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