DESIGN OF INTEGRAL SLIDING MODE OBSERVERS FOR STATE, FAULT AND UNKNOWN INPUT RECONSTRUCTION
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Bibliographic record
Abstract
This paper proposes a new technique for fault diagnosis and estimation of states and unknown inputs in a class of nonlinear systems. The novelty of this approach lies in the design of two nonlinear observers which incorporate a combination of sliding and integral control actions. The observers are networked together for online information interchange. The first observer is used for fault diagnosis, and the second is used for the unknown inputs. It is shown that under certain conditions, the proposed observer is able to reduce chattering without compromising on estimation accuracy. Another significant advantage of the proposed approach is that the network of two interconnected integral sliding mode observers permits the relaxation of the fault isolability from the unknown inputs (in an appropriate sense), which has been a major problem previously.
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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