Model-Free Adaptive Control for Three-Dimensional Crane Systems
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Bibliographic record
Abstract
This paper proposes the development of and validation of a Model-Free Adaptive Control (MFAC) algorithm for a three-dimensional crane system in a multi input-multi output setting. The three-dimensional cranes are complex systems with various nonlinearities providing a robust environment for testing the adaptability and efficiency of the MFAC algorithms. The paper aims to compare two distinct versions of the algorithm, i.e., the compact form dynamic linearization (CFDL) and the partial form dynamic linearization (PFDL). Both versions are analyzed in terms of their performance in controlling the three-dimensional crane’s movement by controlling the x, y, and z-axes under varying conditions. Experimental validation highlights the strengths and limitations of CFDL and PFDL versions, offering insights into their practical applications and theoretical underpinnings.
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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 | 0.000 |
| 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