Event-Triggered Multiobjective Control and Fault Diagnosis: A Unified Framework
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it