Fault‐tolerant control of nonlinear process systems subject to sensor faults
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Bibliographic record
Abstract
Abstract The problem of control of nonlinear process systems subject to input constraints and sensor faults (complete failure or intermittent unavailability of measurements) is considered. A fault‐tolerant controller is designed that utilizes reconfiguration (switching to an alternate control configuration) in a way that accounts for the process nonlinearity, the presence of constraints and the occurrence of sensor faults. To clearly illustrate the importance of accounting for the presence of input constraints, first the problem of sensor faults that necessitate sensor recovery to maintain closed‐loop stability is considered. We address the problem of determining, based on stability region characterizations for the candidate control configurations, which control configuration should be activated (reactivating the primary control configuration may not preserve stability) after the sensor is rectified. We then consider the problem of asynchronous measurements, that is of intermittent unavailability of measurements. To address this problem, the stability region (that is, the set of initial conditions starting from where closed‐loop stabilization under continuous availability of measurements is guaranteed), as well as the maximum allowable data loss rate which preserves closed‐loop stability for the primary and the candidate backup configurations are computed. This characterization is utilized in identifying the occurrence of a destabilizing sensor fault, and in activating a suitable backup configuration that preserves closed‐loop stability. The proposed method is illustrated using a chemical process example and demonstrated via application to a polyethylene reactor. © 2007 American Institute of Chemical Engineers AIChE J, 2007
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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 | 0.001 | 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