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Record W2904728798 · doi:10.1002/rnc.4430

A reconfiguration control framework for constrained systems with sensor stuck faults

2018· article· en· W2904728798 on OpenAlex
Domenico Famularo, Giuseppe Franzè, Walter Lúcia, Cristina Manna

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 Robust and Nonlinear Control · 2018
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl reconfigurationControl theory (sociology)Bounded functionFault toleranceComputer scienceFault detection and isolationScheme (mathematics)Equivalence (formal languages)Model predictive controlSet (abstract data type)Control (management)Invariant (physics)MathematicsDistributed computingActuatorArtificial intelligenceEmbedded system

Abstract

fetched live from OpenAlex

Summary In this paper, a sensor stuck fault‐tolerant control framework for linear time‐invariant plant models subject to input/state constraints and bounded disturbances is presented. A receding horizon control reconfigurable scheme is proposed to contrast undesired effects due to sensors malfunctioning. The main merit of this strategy relies on its intrinsic capability to quickly identify fault occurrences and to take a decision on the adequate control action. This is formally obtained by jointly exploiting set‐theoretic polyhedral ideas and the certainty equivalence concept. A numerical example is provided and the control performance contrasted with a well‐reputed competitor fault‐tolerant control 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 categoriesnone
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 score0.875
Threshold uncertainty score0.510

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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