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Record W4205183916 · doi:10.1002/acs.3369

Adaptive fixed‐time fuzzy control for nonlinear systems with actuator faults

2022· article· en· W4205183916 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

VenueInternational Journal of Adaptive Control and Signal Processing · 2022
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)BacksteppingActuatorNonlinear systemBounded functionFuzzy logicController (irrigation)Computer scienceAdaptive controlTracking errorFuzzy control systemControl engineeringMathematicsEngineeringControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

Summary This article copes with the adaptive fixed‐time funnel control problem for a class of nonlinear systems with actuator faults. To deal with the difficulties due to actuator faults, which include both lock‐in‐place and loss‐of‐effectiveness models, an adaptive fault‐tolerant control scheme is proposed. By introducing the fuzzy logic system and backstepping technique, an adaptive fixed‐time controller is developed to ensure that the tracking error converges into a pre‐specified performance funnel within a fixed time, which is independent on the initial state, and in the meantime, the controlled closed‐loop system remains semi‐global fixed‐time bounded stable and all the signals are bounded. Simulation results verify the proposed approach.

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)0.000
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 score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.222
Teacher spread0.211 · 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