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Record W2320459051 · doi:10.1109/tii.2016.2541669

Event-Triggered Multiobjective Control and Fault Diagnosis: A Unified Framework

2016· article· en· W2320459051 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 Industrial Informatics · 2016
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsConcordia University
FundersQatar National Research Fund
KeywordsComputer scienceEvent (particle physics)AlgorithmPhysics

Abstract

fetched live from OpenAlex

In the area of robust control, fault diagnosis, and fault tolerant control of linear systems, many fundamental problems can be recast as H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> , I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and generalized H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> control frameworks leading to the so-called mixed norm or multiobjective optimization problems. This paper develops a new linear matrix inequality (LMI) approach to the problems of event-triggered multiobjective synthesis of feedback controllers and fault diagnosis filters through a unified framework. Toward this end, at first a general problem known as event-triggered integrated fault detection, isolation and control (E-IFDIC) is defined. By utilizing a filter to represent, characterize, and specify the E-IFDIC module, a multiobjective formulation of the problem is developed based on H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> , H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sub> , I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and generalized H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> performance criteria. It is shown that when an event-triggered strategy is applied to both the sensor and E-IFDIC module, the amount of data that is sent through the sensor-to-E-IFDIC module and E-IFDIC module-to-actuator channels are dramatically reduced. A set of 'MI feasibility conditions is derived to ensure the solvability of the problem, as well as to simultaneously obtain the E-IFDIC module parameters and the event-triggered conditions. Finally, it is shown that certain existing problems in the fields of time and event-triggered control and fault diagnosis can be considered as special cases of our proposed methodology. Two industrial case studies are also provided to illustrate and demonstrate the effectiveness of our proposed design methodology when compared with available work in the literature.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.723

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 head0.018
GPT teacher head0.234
Teacher spread0.215 · 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