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author:

Lin, Xiufang (Lin, Xiufang.) [1] | Chen, Shumei (Chen, Shumei.) [2] (Scholars:陈淑梅)

Indexed by:

EI Scopus

Abstract:

Magnetorheological (MR) dampers are prominent semi-active control devices for vibration mitigation of structures which undergo severe loads such as earthquakes or strong winds. However, because of their inherent non-linear characteristics, development of control strategies that can fully exploit the capabilities of MR dampers is an important and challenging task. In this study, an intelligent control strategy integrating fuzzy logic controller and Modified Shuffled Frog-Leaping Algorithm (MSFLA) is proposed to reduce seismic responses of structures installed with MR dampers. The MSFLA is used to adaptively optimise the FLC parameters including Membership Function (MF) parameters, fuzzy rules and input scaling gains. The MSFLA-optimised FLC is employed to establish optimal relationship between seismic responses and command voltages of MR dampers. Simulation results verify that the proposed controller outperforms clipped-optimal control and fuzzy control methods. Also, the proposed controller can deal with changes in structural parameters and earthquake excitations. Copyright © 2016 Inderscience Enterprises Ltd.

Keyword:

Computer circuits Controllers Earthquakes Fuzzy control Fuzzy inference Fuzzy logic Membership functions Seismic response Structural dynamics

Community:

  • [ 1 ] [Lin, Xiufang]College of Mechanical Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Lin, Xiufang]Department of Information and Mechatronics Engineering, Jianshan College of Fujian Agricultural and Forrest University, Fuzhou; 350002, China
  • [ 3 ] [Chen, Shumei]College of Mechanical Engineering, Fuzhou University, Fuzhou; 350116, China

Reprint 's Address:

  • 陈淑梅

    [chen, shumei]college of mechanical engineering, fuzhou university, fuzhou; 350116, china

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Source :

International Journal of Computer Applications in Technology

ISSN: 0952-8091

Year: 2016

Issue: 3

Volume: 53

Page: 279-289

1 . 2 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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