An optimal MRAC–ASMC scheme for robot manipulators based on the artificial bee colony algorithm
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Bibliographic record
Abstract
In this paper, an optimal multi-adaptive robust controller is proposed for robot manipulators using the gradient descent method and artificial bee colony. At first, model reference adaptive control (MRAC) and sliding mode control (SMC) are separately designed for handling a robot manipulator with two revolute (2R) joints. Further, the coefficients of the sliding surfaces and control efforts are updated via a suitable adaptive mechanism based on the gradient descent method. In addition, to minimize the weighted summation of integral time absolute error (ITAE), some constant parameters of the controllers are determined by the artificial bee colony optimization algorithm. Finally, comparisons and performance tests are illustrated to demonstrate the effectiveness and superiority of the proposed control scheme for trajectory tracking in comparison with other traditional approaches.
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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 | 0.001 |
| 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