A Unit-Gain D-type Iterative Learning Control Scheme: Application to a 6-DOF Robot Manipulator
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Bibliographic record
Abstract
In this paper, a novel method to realize a unit-gain feature in iterative learning control (ILC) is proposed, using both forward and backward filtering. Based on this method, a unit-gain derivative is proposed as a remedy to the undesirable high gain feature of the conventional derivative at high frequency. The scheme is equivalent to an all-pass unit-gain phase shifter; the forward altering uses a 0.5-order derivative and the backward filtering employs a 0.5-order integral. The all-pass phase shifter is then deployed in a unit-gain D-type ILC. For implementation, frequency-band synthesis of non-integer differentiator is introduced. The effectiveness of the unit-gain D-type ILC is demonstrated by experimental results on a 6 DOF robot manipulator.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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