A Model-Driven Realization of AUV Controllers Based on the MDA/MBSE Approach
Bibliographic record
Abstract
This paper introduces a model-driven control realization, which is based on the systems engineering concepts of the model-driven architecture (MDA)/model-based systems engineering (MBSE) approach combined with the real-time UML/SysML, extended/unscented Kalman filter (EKF/UKF) algorithms, and hybrid automata, in order to conveniently deploy controllers of autonomous underwater vehicles (AUVs). This model also creates a real-time communication pattern, which can permit the designed components to be customizable and reusable in new application developments of different AUV types. The paper brings out stepwise adapted AUV dynamics for control that are then combined with the specialization of MDA/MBSE features as follows: the computation independent model (CIM) is defined by the specification of the use-case model together with hybrid automata to gather the requirement analysis for control; the platform-independent model (PIM) is then designed by specializing the real-time UML/SysML’s features including main control capsules that depict structures and behaviors of controllers in detail; and the detailed PIM is subsequently converted into the platform-specific model (PSM) by object-oriented platforms to rapidly implement the AUV controller. Based on this proposed model, a horizontal planar trajectory-tracking controller was deployed and tested that permits a miniature AUV possessing a torpedo shape to reach and follow the desired horizontal planar trajectory.
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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".