Active Roll Control of Heavy Single Unit Vehicles Employing MEMS Angular Rate Sensors
Bibliographic record
Abstract
The present paper is concerned with the use of active roll control to improve the roll stability of heavy road-vehicles and the application of Micro-electro-mechanical System (MEMS) angular rate sensors in the feedback monitoring. For this purpose, mathematical models that represent the roll/yaw dynamics for a torsionally rigid Single Unit Vehicle (SUV) is presented. The state-space models that represent the vehicle dynamics are also developed for the purpose of performing numerical simulations. A linear Quadratic Gaussian (LQG) based controller, using Kalman estimator to estimate certain states, is employed to design a full-state active roll control system. A mathematical model that represents the dynamic behavior of a low-cost MEMS gyroscope is derived for the purpose of investigating the suitability of applying this class of angular rate sensor in the roll control of heavy vehicles. Some reliability issues related to MEMS sensors, such as noise and drift, are introduced and included in vehicle dynamic models.
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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".