A model of hybrid systems and their transition dynamics
Bibliographic record
Abstract
Hybrid systems (HS) provide a new formalism for dynamical systems and control theory which bridges a gap between continuous-time and discrete-event systems. In this paper, we examine phenomena arising in general systems for which hybrid systems would appear to be an appropriate formalism. A hybrid model is adopted that provides a means of capturing hybrid-type phenomena and behaviour of interest. This model couples a finite control automaton with a continuous-time plant through analog-to-digital and digital-to-analog converters, with the automaton and plant interacting only at fixed sample times. Within this modelling formalism, the following customizations are made: (i) the specification of three admissible control law classes, (ii) the provision of a setting to consider three forms of uncertainty referred to as transition dynamics, structural uncertainty, and parametric uncertainty. We introduce various models of transition dynamics that characterize varying levels of knowledge or certainty about the system dynamics during some transition period.
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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".