Comparison of Control Approaches For Tracking Control of a 3 DOF Parallel Robot: Experimental Results
Bibliographic record
Abstract
In this paper, to study the effect of different control approaches on improving trajectory tracking accuracy for a 3 degree-of-freedom (DOF) planar parallel robot, we tested two synchronized-type controllers: PI-type synchronized control and adaptive synchronized (A-S) control; and conventional PID control and adaptive control. Here PID control and PI-type synchronized control are dynamic model-free while the adaptive control and A-S control are dynamic model-based. Because of the closed-loop kinematic chain mechanism of the experimental planar parallel robot used in this study, trajectory tracking control of this robot may be treated as a synchronization problem, and consequently, use of the synchronized control approaches can substantially improve the trajectory tracking performance of the robot end-effector compared with approaches without synchronization. Through conducting experiments on an experimental 3-DOF P-R-R type planar parallel robot by using the four control approaches, the above claims are demonstrated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".