Adaptive Non-singular Fast Terminal Sliding Mode Control for Car-Like Vehicles with Faded Neighborhood Information and Actuator Faults
Bibliographic record
Abstract
Abstract This study addresses the problem of cooperative control design for a group of car-like vehicles encountering fading channels, actuator faults, and external disturbances. It is presumed that certain followers lack direct access to the states of the leader via a directed graph. This arises challenges in maintaining synchronization and coordination within the network. The proposed control strategy utilizes non-singular fast terminal sliding mode control to accelerate consensus tracking and enhance the convergence of the overall system. This controller is designed to mitigate the impact of actuator faults in the presence of fading channels in the communication network. The effects of such issues on team performance are rigorously analyzed. Based on the Lyapunov stability principle, it has been demonstrated that the controller is capable of providing satisfactory performance for the entire system despite these challenges. Moreover, vehicle synchronization can be effectively maintained. Numerical simulations are conducted to verify the theoretical findings.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".