Sampled-Data Stabilization of a Class of Nonlinear Systems With Application in Robotics
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Bibliographic record
Abstract
Abstract The output feedback stabilization problem for the class of nonlinear Lipschitz systems is considered. A discrete-time feedback controller is designed for the sampled-data case, where the output of the plant is only available at discrete points of time and where the objective is to stabilize the system continuously using a discrete-time controller. We show that exact stabilization in this case can be achieved using a direct sampled-data design approach, based on H∞ optimization theory, in which neither the plant model nor the controller need to be discretized a priori. The proposed design is solvable using commercially available software and is shown to have important advantages over the classical emulation approach that has been used to solve similar problems. The applicability of the proposed techniques in the robotics field is thoroughly discussed from both the modeling and design perspectives.
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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 | 0.000 |
| 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 it