Offset-Free Tracking Control for a Marine Autonomous Surface Ship
Bibliographic record
Abstract
Abstract The importance of autonomous surface vessels is increasing day by day because of more and more missions and safety concerns. An offset-free control system is essential for a Marine Autonomous Surface Ship (MASS) to follow its desired trajectory. The position, yaw angles, and desired velocity are the main parameters that need to be controlled precisely to keep the ship on course in the presence of environmental disturbances. In this current research, we propose an advanced control system for surface vessels that is versatile and can achieve a broad range of operational objectives while obeying safety constraints. A Nonlinear Model Predictive Control (NMPC) is the heart of our proposed system. The NMPC solves a quadratic optimization problem and dynamically calculates the control actions considering the safety constraints of the vessel. The conventional way of calculating the yaw angle and the line-of-sight guidance method for the same are compared when the trajectory tracking results are simulated in the presence of disturbances to test the performance of the controller. Such controllers are expected to provide substantial benefits by providing less operational cost, enhanced safety, and efficiency.
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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) | 0.000 | 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 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".