REMOTE STABILIZATION OF A CLASS OF LINEAR SYSTEMS AND ITS ROBUST STABILITY ANALYSIS
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Bibliographic record
Abstract
In this paper, the stabilization of a class of time delayed remote control systems is first analysed and then designed, using linear matrix inequality techniques. Its robust design with respect to system parametric uncertainties and its robust analysis with respect to nonlinear additive uncertainties as well as time delay uncertainties are discussed. The system under investigation is a cascade system with two subsystems controlled by a remote controller with static gains. The motivation of this work is to explore the problem of distributed networked control systems beginning with the discussion of a simple cascade system. Static controller designs based on delay-dependent stability conditions are presented and are proven to be less conservative than conventional designs. This design is then extended where parametric uncertainties exist. Furthermore, sufficient stability conditions are derived for the system with norm-bounded nonlinear additive uncertainties and time delay variations. Finally, simulation examples are presented to show the effectiveness of the proposed method.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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