Semiactive Nonsmooth Control for Building Structure with Deep Learning

Joint Authors

Wang, Jianhui
Huang, Xiaofang
Zhang, Li
Wang, Qing

Source

Complexity

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-11-06

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Philosophy

Abstract EN

Aiming at suppressing harmful effect for building structure by surface motion, semiactive nonsmooth control algorithm with Deep Learning is proposed.

By finite-time stable theory, the building structure closed-loop system’s stability is discussed under the proposed control algorithm.

It is found that the building structure closed-loop system is stable.

Then the proposed control algorithm is applied on controlling the building structural vibration.

The seismic action is chosen as El Centro seismic wave.

Dynamic characteristics have comparative analysis between semiactive nonsmooth control and passive control in two simulation examples.

They demonstrate that the designed control algorithm has great robustness and anti-interference.

The proposed control algorithm is more effective than passive control in suppressing structural vibration.

American Psychological Association (APA)

Wang, Qing& Wang, Jianhui& Huang, Xiaofang& Zhang, Li. 2017. Semiactive Nonsmooth Control for Building Structure with Deep Learning. Complexity،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1143252

Modern Language Association (MLA)

Wang, Qing…[et al.]. Semiactive Nonsmooth Control for Building Structure with Deep Learning. Complexity No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1143252

American Medical Association (AMA)

Wang, Qing& Wang, Jianhui& Huang, Xiaofang& Zhang, Li. Semiactive Nonsmooth Control for Building Structure with Deep Learning. Complexity. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1143252

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1143252