Fictitious Reference Iterative Tuning of Discrete-Time Model-Free Control for Tower Crane Systems
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Bibliographic record
Abstract
The purpose of this paper is to propose a novel controller that is based on a combination of two data-driven algorithms, namely the Fictitious Reference Iterative Tuning (FRIT) algorithm and the Model-Free Adaptive Control (MFC) algorithm while considering a particular form of MFC, that is the intelligent proportional-integral-derivative (iPID) controller.The main advantage of this combination is that the FRIT algorithm optimally tunes the parameters of the iPID controller by solving an optimization problem based on a metaheuristic African Vultures Optimization Algorithm (AVOA).The novel controller, referred to as the FRIT-iPID controller, is validated experimentally on a three-degree-of-freedom tower crane system laboratory equipment in the context of controlling the cart position, the arm angular position and the payload position for this system.
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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 | 0.000 |
| 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