Fault-Tolerant Cooperative Control Design for Car-Like Vehicles Subject to Actuator Faults and Fading Channels
Bibliographic record
Abstract
This brief addresses the problem of fault-tolerant cooperative control (FTCC) for a group of car-like vehicles experiencing actuator faults. The main feature of this study is the transmission of vehicle’s state information via fading channels. It is challenging to compensate for actuator faults and maintain vehicle’s stability in the presence of unreliable communication links. To cope with such fault conditions, this work introduces an integral terminal sliding mode control developed by means of received faded neighborhood state information. The fading channel’s effect and the nonlinearity of vehicle dynamics are carefully analyzed by providing rigorous proofs with the Lyapunov stability theorem. In this study, the settling time function relies on design parameters rather than the initial states, which is essential for real applications. The effectiveness of the proposed controller is validated in a real system using the latest Quanser self-driving car (QCar) platform.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".