Backstepping and Sliding Mode Control for AUVs Aided with Bioinspired Neurodynamics
Why this work is in the frame
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Bibliographic record
Abstract
Research on tracking control has been on-going for many years. The accuracy and the practicality of the tracking control method has always been one of the most important aspects when designing the control strategy. Autonomous Underwater Vehicles are becoming increasingly important in the applications of ocean surveillance and military, etc. Therefore, this paper aims to develop a control method for autonomous underwater vehicles based on bioinspired neural dynamics. The proposed method practically solves the speed jump and chattering issues that are respectively in conventional backstepping and sliding mode controls with the aid of the bioinspired neural dynamics. In addition, the proposed control method also takes the dynamic uncertainties for the autonomous underwater vehicle into the consideration. The combined tracking method has relatively good overall performance for autonomous underwater vehicle against model uncertainties and disturbances.
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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