An optimal robust controller for active trailer differential braking systems of car-trailer combinations
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents an optimal robust controller for active trailer differential braking (ATDB) systems of car-trailer (CT) combinations. To design ATDB systems, controllers based on the linear quadratic regulator (LQR) technique have been explored. In these LQR controller designs, vehicle forward speed, trailer payload, etc., were assumed as constants. In reality, a CT combination is frequently confronted with variations of operating conditions and vehicle parameters, which may impose significant impacts on the lateral stability of these vehicles. This motivates the investigation into robust controller designs. An ATDB controller is designed using the µ synthesis technique. A new method using a genetic algorithm (GA) for tuning the weighting function parameters for the robust controller is presented. In the parameters tuning process, the lateral stability is emphasised and the path-following capability is considered. Simulation results confirm the validity of the ATDB controller.
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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 | 0.000 | 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 it