Finite-Time Switching Resilient Control for Networked Teleoperation System With Time-Varying Delays and Random DoS Attacks
Bibliographic record
Abstract
This paper presents a finite-time switching resilient controller for the networked teleoperation system control under time-varying delays and denial-of-service (DoS) attacks. The proposed controller comprises a proportional-differential plus damping (PD+d-like) controller and a switching resilient compensator. The first component, a PD+d-like controller, uses a continuous non-smooth function on the state errors and velocity signals to guarantee the global finite-time convergence. The latter part of the proposed controller, a switching resilient compensator, combines the zero-order holder (ZOH) with the continuous-time proportional-derivative (PD) regulator. This proposed controller could maintain global finite-time stability (GFTS) when time-varying delays and random DoS attacks simultaneously occur. Furthermore, we obtain the system stability criterion and establish relationships between controller parameters and maximum stability delay using Linear Matrix Inequality (LMI) technology for parameter tuning guidance. Both simulation and experimental results validate the resiliency of the proposed controller to time-varying delays and random DoS attacks.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".