Gain tuning of position domain PID control using particle swarm optimization
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Bibliographic record
Abstract
SUMMARY Particle swarm optimization (PSO) is a heuristic optimization algorithm and is commonly used for the tuning of PD/PID-type controllers. In this paper, PSO is applied for control gain tuning of a position domain PID controller in order to improve contour tracking performances of linear and nonlinear contours for a serial multi-DOF robotic manipulator. A new fitness function is proposed for gain tuning based on the statistics of the contour error, and pre-existed fitness functions are also applied for the optimization process, followed by some comparison studies. The PSO tuning technique demonstrated the same effectiveness in position domain controllers as in time domain controllers with the results being quite satisfying with low contour errors for both linear and nonlinear contours, and the proposed fitness function is proved to be on par with the pre-existed fitness functions.
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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