A Bioinspired Filtered Backstepping Tracking Control of 7000-m Manned Submarine Vehicle
Bibliographic record
Abstract
In this paper, a new approach of tracking control is investigated for the 7000-m Jiaolong manned submarine vehicle (MSV). First, the formulation of control allocation problem and some background information about tracking control of the 7000-m Jiaolong MSV are presented. Then, a kinematic controller is derived. The filter design using bioinspired model is employed to handle the speed jump problem and to make sure that each thruster is within the saturation limit. The kinematic controller is then extended to incorporate a sliding-mode control technique to complete the dynamic control. The system stability is guaranteed, and tracking errors asymptotically converge to zero by Lyapunov stability theory. Another interesting phenomenon is that the bioinspired method can achieve more satisfactory tracking result with a less control effort compared to a typical backstepping method. Finally, simulations illustrate the performance of the derived cascaded tracking control technique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".