MétaCan
Menu
Back to cohort
Record W2075498933 · doi:10.1109/tcst.2011.2162646

A QFT-Based Decentralized Design Approach for Integrated Fault Detection and Control

2011· article· en· W2075498933 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 · 2011
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBenchmark (surveying)Fault detection and isolationActuatorRelation (database)Control engineeringControl theory (sociology)Multiplicative functionEngineeringComputer scienceGRASPControl (management)MathematicsData miningArtificial intelligence

Abstract

fetched live from OpenAlex

A novel practically implementable design approach is presented for integrated fault detection and control (IFDC) of uncertain systems. The desired constraints in relation to fault detection (FD) and control objectives are simultaneously considered throughout the design, and mapped to equivalent graphical bounds in Nichols chart. The resulting feedback law is obtained through an interactive loop-shaping technique such that the design bounds are satisfied. The proposed graphical design approach has a number of exclusive benefits from engineering perspective, in terms of simplicity and applicability to a large variety of fault types and models, that are discussed in this paper. The effectiveness of the proposed technique is experimentally assessed using the Three-Tank, Amira DTS200, benchmark system in the presence of multiplicative actuator and sensor faults.

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 score0.990
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 integrity0.0010.000
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 head0.016
GPT teacher head0.204
Teacher spread0.188 · 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