ROBUST CONTROL DESIGN FOR A PLANAR PARALLEL ROBOT
Why this work is in the frame
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Bibliographic record
Abstract
In this paper a control design approach termed the Convex Integrated Design (CID) method is used to design a robust controller for a high-speed, high-accuracy planar parallel robot. A controller that simultaneously satisfies four closed-loop performance specifications---the first three define closed-loop performance (i.e. the high-speed and high-accuracy motion of the platform with a limited control effort) and the fourth is a robustness specification that guarantees the previous three closed-loop performance specifications are satisfied in the presence of dynamic model uncertainty (e.g., unknown payload) and external disturbances---is determined using the CID method. Experimental results are presented that verify both the performance of the resultant control design and the CID method, applied to this planar parallel 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 | 0.000 |
| 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