Acceleration-Based Vibration Control for Structural Systems with Actuator Faults and Finite-Time State Constraint
Bibliographic record
Abstract
The problem of acceleration-based vibration control for structural systems with actuator faults and finite-time state-constraint is discussed in this paper. The objective of designing controllers is to guarantee the closed-loop systems satisfying a finite-time state-constraint condition while having a prescribed level of acceleration attenuation performance. First, by describing the actuator faults into a fault matrix, the actuator-fault-included state-space model, with the acceleration as its controlled output, is obtained. Then, based on a combination of matrices and rank-1 vectors, the obtained model is extended to its uncertain description which contains parameter uncertainties appearing in all the mass, damping and stiffness matrices. Second, based on the finite-time stability analysis, the sufficient conditions for the existence of acceleration-based vibration controllers are obtained. By solving these conditions, the desired controllers, with considerations of actuator faults and parameters uncertainties, are obtained for the closed-loop system to be stable with finite-time state-constraint and acceleration-based H-infinite performance. In the end, simulation results are given to show the effectiveness of the proposed theorems.
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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) | 0.000 | 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) | 0.001 | 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".