Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system
Why this work is in the frame
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Bibliographic record
Abstract
In this study, a multi-objective artificial bee colony (MOABC) optimization algorithm was utilized to improve the performance of an adaptive robust control technique. This approach is implemented using an inverted pendulum system. More precisely, the proposed controller is a combination of a decoupled sliding-mode controller (DSMC) and adaptation laws based on the gradient descent approach. To achieve optimum control operation, the MOABC, as a novel meta-heuristic method simulated from the smart foraging activity of honeybee groups, was employed to optimize the coefficients of the suggested controller. In this regard, the objective functions are determined as the integral time of the absolute value of the pole angle and cart position errors. Finally, the time responses of the system states and control effort are presented to prove the effectiveness and feasibility of the proposed strategy compared with other contemporary studies referenced in this paper.
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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) | 0.001 | 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