Actuator fault detection and estimation for linear hyperbolic PDEs with Fredholm integrals
Bibliographic record
Abstract
This paper considers the actuator detection and estimation problem for a class of linear first-order hyperbolic partial integral differential equation (PIDE) systems. Based on the fault detectability analysis, a Luenberger-type observer is employed to achieve fault detection. However, in the case of actuator fault occurrence, modified Luenberger-type observers are developed such that actuator fault estimation is achieved in the presence of actuator fault while the system state estimation is realized. In comparison to the existing filter-based methods for distributed parameter systems, in proposed method in this manuscript, it is not necessary to transform the plant into the observer canonical form. The advantage of the proposed method is its flexible extension to other linear distributed parameter systems including all Riesz-spectral systems, as well as higher order nonspectral hyperbolic PDE systems. In particular, the proposed method is applicable to stable or unstable plants since the corresponding observation error systems are always stable, and therefore faults as well as plant state can be adequately estimated. Finally, an illustrative example is present to verify theoretical results.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".