Resilient Control of CPSs Under Mixed DoS Attacks: A Type-Dependent ADT Approach
Bibliographic record
Abstract
This article studies the resilient control against mixed denial of service (DoS) attacks for cyber-physical systems (CPSs). Different from existing results, this work considers the presence of both zero- and hold-input attacks, where a unified model is introduced to describe mixed DoS attacks. Upon this model, the original CPS is reformulated as a switched system subject to a time-varying delay. To characterize the occurrence frequency and duration of zero- and hold-input attacks, the type-dependent average dwell time (ADT) switching is adopted. In the meantime, multiple discontinuous Lyapunov functions (MDLFs) suitable to the type-dependent ADT switching are employed. By virtue of the switching scheme and MDLFs, a piecewise feedback controller is designed to guarantee global uniform exponential stability and$H_\infty$performance of the closed-loop system. In addition, the developed control law is extended to an observer-based version, accommodating the case when the system state is not fully measurable. Finally, the effectiveness of our theoretical results is verified by two numerical examples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".