Analysis and Control of an Actuation-Redundant Parallel Mechanism Requiring Synchronization
Bibliographic record
Abstract
Abstract Presented in this paper is a method for analysis and control of an actuation-redundant parallel mechanism requiring synchronization. The said mechanism is made up of two branches that are connected to drive a common end-effector with only one degree-of-freedom of motion. The two actuators must share the load exerted on the common end-effector during motion. The underlying problem is to synchronize the motion of the two actuators while balancing the forces on them so that the entire mechanism can move smoothly under the applied load on the end-effector. Due to the space limitation, the two branches are geometrically different leading to opposite force profiles for the two actuators. The proposed method combines the mechanism kinematics with force analysis. First, a closed-form solution is derived that relates the actuator strokes to the rotation angle of the end-effector. Second, a velocity relationship is obtained to relate the actuator velocities to the angular velocity of the end-effector. Third, a force relationship is established relating the actuator loads to the external load. Fourth, a control strategy is designed to synchronize the motion of the two actuators while maintaining the force balance between them to avoid the problem of motion mismatching and force fighting that could lead to the failure of the mechanism. A prototype was built and tested with the proposed method, which is also presented in this paper.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".