Path-Following Control of an AUV: A Multiobjective Model Predictive Control Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The path-following (PF) problem of an autonomous underwater vehicle (AUV) is studied, in which the path convergence is viewed as the main task while the speed profile is also taken into consideration as a secondary task. To accommodate the prioritized PF tasks, a novel multiobjective model predictive control (MPC) (MOMPC) framework is developed. Two methods, namely, weighted sum (WS) and lexicographic ordering, are investigated for solving the MOMPC PF problem. A logistic function is proposed for the WS method in an attempt to automatically select the appropriate weights. The Pontryagin minimum principle is subsequently applied for the WS-MOMPC implementation. The implicit relation between the two methods is shown, and the convergence of the solution with the MOMPC PF control algorithms is analyzed. Simulation studies on the Saab SeaEye Falcon AUV demonstrate the effectiveness of the proposed MOMPC PF control.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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