A switching supervisory control design for uncertain discrete time-delay systems
Bibliographic record
Abstract
This paper presents an adaptive switching supervisory control scheme for highly uncertain discrete-time systems with time-varying state delay and time-varying parameters. The uncertainties appear in the system matrices and the system is assumed to be subject to the external bounded disturbances. It is supposed that a set of stabilizing controllers are available (which are designed off-line) to stabilize the system in the whole uncertain parameter space. To find a supervisory control scheme, it is initially assumed that the system parameters and delay are fixed. A switching algorithm is then proposed to stabilize the system. Next, by modifying the proposed algorithm, the stability analysis of the system with time-varying parameters and time-varying delay is carried out. Furthermore, an upper bound on the permissible rate of change of the system parameters and delay to maintain stability of the closed-loop system is obtained. Simulation results are presented to show the efficacy of the proposed switching scheme.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".