2020
DOI: 10.1061/ajrua6.0001085
|View full text |Cite
|
Sign up to set email alerts
|

Kriging-Based Design for Robust High-Performance Control Systems

Abstract: High-performance control systems (HPCS) are sophisticated vibration-mitigation devices that include active, semiactive, and hybrid systems. HPCS leverage feedback mechanisms to dynamically adjust the damping force in response to motion, offering a good mitigation performance over a wide excitation bandwidth. These damping systems are attractive for multihazard mitigation of civil structures. However, the application of HPCS necessitates the design and integration of a closed-loop control system that can be sus… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2020
2020
2022
2022

Publication Types

Select...
4
1

Relationship

2
3

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 53 publications
0
2
0
Order By: Relevance
“…Synthetic input/output observations are usually derived from numerical simulation models, which might lead to approximate responses. Furthermore, when the response of the structure is highly nonlinear, a large data pool might be required to train a reliable surrogate model [15][16][17], yielding a significant computational burden. A solution to this drawback could be to extract input/output observations directly from field data [18].…”
Section: Introductionmentioning
confidence: 99%
“…Synthetic input/output observations are usually derived from numerical simulation models, which might lead to approximate responses. Furthermore, when the response of the structure is highly nonlinear, a large data pool might be required to train a reliable surrogate model [15][16][17], yielding a significant computational burden. A solution to this drawback could be to extract input/output observations directly from field data [18].…”
Section: Introductionmentioning
confidence: 99%
“…Micheli et al [34] investigated the use of Kriging surrogate and adaptive wavelet network (AWN) metamodels for the uncertainty quantification of a semi-active control system. The authors concluded that the AWN provided a fast and reliable estimation of the average system response, while the Kriging could be used for a robust design of the control system, later developed in Micheli et al [35] In all of the surveyed applications, the use of surrogate models as a replacement of the original numerical simulation model yielded a significant reduction in the computational demand for the performed tasks.…”
mentioning
confidence: 99%