Design of a Fuzzy Controller for an Underwater Vehicle Aiming at a Stationary Target
Bibliographic record
Abstract
In this paper, on the basis of a robust algorithm for the analysis of the 6 DOF motion of an underwater vehicle in calm water, after presenting the dynamics model and simulating motion, the model is put in the closed loop control to perform a controlled mission. The mission is defined as to navigate the submarine toward a desired point in the vertical plane. In performing the mission, the least time and of course the least position error with respect to the target point is aimed. The designed controller based on fuzzy logic and thus adapted to the human patterns for navigation, with a simple structure, performs the mission accurately. The intelligent structure of the fuzzy controller, results in a spectacular capability in target finding; such that by the increase of mission duration, the submarine, which never completely stops in this modeling, reaches the target point multiple times. Several simulations of the controlled motion, changing the coordinates of target point, proved the controller effectiveness.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".