Stable Iterative Correlation-based Tuning algorithm for servo systems
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Bibliographic record
Abstract
This paper proposes an iterative Correlation-based Tuning (CbT) algorithm which guarantees the control system stability throughout the iterations. The new algorithm is based on a Robbins-Monro procedure which ensures the iterative tuning of controller parameters such that to minimize a cost function expressed as the squared sum of the cross-correlation function between the output error and the reference input. The control system stability is tested using the coprime factor uncertainty of the controller, and the small gain theorem for discrete-time systems is applied. Nonparametric frequency domain models are employed in the calculation of the bounds on systems' gains. A case study concerning the speed control of a nonlinear servo system is included to validate the new stable CbT algorithm, and experimental results are given.
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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