Semi-Active Adaptive Fuzzy Sliding Mode Control of Buildings under Earthquake Excitations
Bibliographic record
Abstract
New Adaptive Fuzzy Sliding Mode Control (AFSMC) method is proposed for semi-active control of buildings under earthquake excitations. The proposed method has the important advantage of being model-free, and therefore, can cope with uncertainties in the structural model, high nonlinearities in the behaviour of MagnetoRheological (MR) dampers and the random nature of the earthquake excitations. The proposed approach encompasses a fuzzy system and a robust controller. The fuzzy system mimics an ideal sliding-mode controller, and the robust controller compensates for the difference between the fuzzy controller and the ideal one. The parameters of the fuzzy system, as well as the uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the asymptotic stability of the controlled system. The AFSMC controller determines the needed control force, and an internal force-following loop approximately generates the required interaction force by intermittent activation of the semi-active dampers (Clipped algorithm). A three-story benchmark building with only one MR damper in the first floor is considered. By comparing the structural responses in the uncontrolled case, AFSMC/Clipped system and an H2-LQG/Clipped control strategy, advantages of AFSMC method are demonstrated.
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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) | 0.000 | 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) | 0.000 | 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".