Sampled-data observer for one-sided Lipschitz systems: Single-rate and multirate cases
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Bibliographic record
Abstract
The problem of sampled-data observer design is addressed for the so-called nonlinear systems with one sided Lipschitz nonlinearity in presence of disturbance inputs. We first develop a single-rate observer using a refined Euler model formulated via tractable linear matrix inequalities (LMIs). This scheme is shown to be input-to-state stable from exogenous disturbances to the estimation error in a semiglobal practical sense for the unknown exact discrete-time plant model. Then, the proposed observer is modified appropriately to cope with the practical case of multirate sampling by preserving similar stability property. A simulation example justifies the efficiency of both observers for the one-sided Lipschitz systems and demonstrates the superiority of the multirate observer when the input and output signals are sampled at different rates.
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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 | 0.001 |
| 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