Model Predictive Control of Asynchronously Switched Systems with Exogenous Disturbances
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Bibliographic record
Abstract
This paper investigates the model predictive control (MPC) problem for a class of asynchronously switched systems with external disturbances. To mitigate the negative impact of additive disturbances, we establish a disturbance mode-dependent dwell time (MDT) invariant (DMI) set which is competent to collect all possible disturbed behaviors in the presence of asynchronous switching. Based on the DMI set, we make use of the tube-based robust MPC (RMPC) methodology to tighten the original constraints. Then, by forcing the state trajectories into an objective zone, the recursive feasibility of the switched MPC design is ensured. Moreover, a terminal target set is designed such that closed-loop asymptotic stability is achieved by imposing this restriction on the reachable sets. A numerical example is provided to verify the theoretical findings.
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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