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Record W3149992929

Adaptive Integral-type Sliding Mode Control for Spacecraft Attitude Maneuvering Under Actuator Stuck Failures

2011· article· en· W3149992929 on OpenAlexaff
HU Qingleia

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)ActuatorSpacecraftIntegral sliding modeInertiaController (irrigation)Fault toleranceAttitude controlAdaptive controlControl engineeringSliding mode controlComputer scienceEngineeringControl (management)Nonlinear systemPhysicsArtificial intelligenceAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

A fault tolerant control (FTC) design technique against actuator stuck faults is investigated using integral-type sliding mode control (ISMC) with application to spacecraft attitude maneuvering control system. The principle of the proposed FTC scheme is to design an integral-type sliding mode attitude controller using on-line parameter adaptive updating law to compensate for the effects of stuck actuators. This adaptive law also provides both the estimates of the system parameters and external disturbances such that a prior knowledge of the spacecraft inertia or boundedness of disturbances is not required. Moreover, by including the integral feedback term, the designed controller can not only tolerate actuator stuck faults, but also compensate the disturbances with constant components. For the synthesis of controller, the fault time, patterns and values are unknown in advance, as motivated from a practical spacecraft control application. Complete stability and performance analysis are presented and illustrative simulation results of application to a spacecraft show that high precise attitude control with zero steady-error is successfully achieved using various scenarios of stuck failures in actuators.

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.

How this classification was reachedexpand

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.052
GPT teacher head0.254
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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