Disturbance Attenuation Trajectory Tracking Control of Unmanned Surface Vessel Subject to Measurement Biases
Why this work is in the frame
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Bibliographic record
Abstract
This article addresses trajectory tracking control of unmanned surface vessels (USVs) subject to position and velocity measurement biases. Unlike model uncertainties and external disturbances, measurement biases can lead to mismatched disturbances in system kinematics, rendering great difficulty to the USV control system design. To overcome this problem, a disturbance attenuation controller was recursively synthesized by incorporating two disturbance observers into the backstepping control design. The stability argument shows that all error signals in the closed-loop system can regulate to the small neighborhoods about the origin. The proposed controller has two remarkable features: (1) By adopting two disturbance observers to estimate the mismatched and matched lumped disturbances, the proposed controller is robust against model uncertainties and external disturbances and insensitive to measurement biases. (2) Meanwhile, the proposed controller is structurally simple and user friendly. Lastly, comparative simulations were conducted to validate the obtained results.
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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) | 0.000 | 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