Enhanced Ball Trajectory Tracking Using Visual Servoing with 2-DOF Ball on Plate Balancing System
Why this work is in the frame
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Bibliographic record
Abstract
Accurate tracking of ball trajectories on a platform using a 2-DOF balancer system poses significant challenges in the existing literature due to its inherent nonlinearity and instability.This research addresses these challenges through a two-fold approach.Firstly, we focus on designing a robust 2-DOF ball balancer system model.Secondly, we perform a comparative study of three control techniques: Linear Quadratic Regulator-based Proportional (LQR_P), Full State Feedback-based Proportional (FSF_P), and Classical Proportional Derivative-based Proportional (PD_P) control.To evaluate the effectiveness of the designed controllers, we conduct both simulation and experimental tests using MATLAB Simulink integrated with Quarc software and the 2DOF ball balancer system Quanser hardware.The results demonstrate that the Linear Quadratic Regulator-based proportional control exhibits superior performance in terms of transient response, including percentage overshoot, settling time, and peak time.Moreover, it showcases excellent steady-state response, achieving a minimum steady-state error of 0.641mm, outperforming the other techniques investigated in this study.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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