Hybrid control approach for seismic coupling of two similar adjacent structures. (4th August 2015)

• Record Type: Journal Article
• Authors: Park, Kwan-Soon; Ok, Seung-Yong
• Is Part Of: Journal of sound and vibration. Volume 349(2015)
• Page Start: 1
• Page End: 17
• Publication Date: 2015-08-04
• Subjects: Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2015.03.028
• Languages: English
• ISSNs: 0022-460X

Abstract

Abstract: This study describes an optimal hybrid control approach of two similar adjacent buildings for seismic performance improvement, for which the passive dampers are used as link members between the two parallel buildings and the active control devices are installed as tendon-type devices between two successive floors in the buildings. Throughout this configuration, the passive coupling dampers modulate the relative responses between the two buildings and the active control devices modulate the inter-story responses of each building. In order to achieve global optimal control performance, genetic algorithm is employed to perform an integrated design approach for the system of buildings and hybrid control devices. Through the optimization process, the passive and active devices are optimally distributed along the floors and, simultaneously, their damping capacities and active controllers are configured in accordance with the distribution. The proposed approach is demonstrated in comparison with typical active control system which consists of two independent active systems without any connections between two buildings, each being optimal for one particular building. The numerical simulation results for a system of 20-story and 16-story buildings reveal that the proposed system can guarantee the competent control performance over the typical independent active system with less control forces and powers. As a result, it is proved that the proposed approach enables the simultaneous optimization of the control performance and the control cost.