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Record W2169643615 · doi:10.1109/cdc.2001.981182

A stability guaranteed active fault-tolerant control system against actuator failures

2003· article· en· W2169643615 on OpenAlexaff
Midori Maki, Jin Jiang, Kouichi Hagino

Bibliographic record

VenueProceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228) · 2003
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsFault toleranceRedundancy (engineering)ActuatorControl theory (sociology)Computer scienceControl engineeringControl (management)Stability (learning theory)Fault detection and isolationControl systemEngineeringReliability engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

A strategy is proposed for fault-tolerant control system (FTCS) design using multiple controllers. The design of such multiple controllers is shown to be unique in the sense that the resulting control system does neither have the problem of conservativeness of conventional passive fault-tolerant control (FTC) nor the risk of instability associated with active FTCS in case of an incorrect fault detection and isolation (FDI) decision. In other words, the stability of the closed-loop system is always ensured regardless the FDI decisions. The correct FDI decision will further lead to optimal performance of the system. The paper presents an interesting way to deal with the conflicting requirements among stability, redundancy, and graceful degradation in performance for fault-tolerant control systems. Detailed design procedure has been presented with consideration of possible parameter uncertainties.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.207
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)Same topicFault Detection and Control SystemsFrench-language works237,207