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Nonlinear decentralized control of seismically excited civil structures

  • Jian Wang*
  • , Hui Li
  • , Luyu Li
  • , Gangbing Song
  • *Corresponding author for this work
  • School of Civil Engineering, Harbin Institute of Technology
  • University of Houston
  • Dalian University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The dynamic behaviour of civil structures under strong earthquakes is usually nonlinear or inelastic. Conventional control approach is almost based on linear theory, such as the linear quadratic regulator (LQR) design. One of the common characteristics shared by seismically excited civil structures is a distinct subsystem property, which indicates there are only several floors of civil structures with nonlinear or inelastic vibration and the other with linear vibration. In this study, a robust control approach combining decentralized control with adaptive fuzzy control is proposed to treat the nonlinear control for civil structures. The structural system is decomposed into several artificially subsystems, while the different subsystem is adopted the corresponding control algorithm. The input-to-state stability of the entire system can be guaranteed by the proposed control method, and an H infinity performance is achieved through a subsystem with the proposed controller. Numerical examples are presented to demonstrate the effectiveness and robustness of the proposed controller.

Original languageEnglish
Title of host publicationActive and Passive Smart Structures and Integrated Systems 2009
DOIs
StatePublished - 2009
Externally publishedYes
EventActive and Passive Smart Structures and Integrated Systems 2009 - San Diego, CA, United States
Duration: 9 Mar 200912 Mar 2009

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7288
ISSN (Print)0277-786X

Conference

ConferenceActive and Passive Smart Structures and Integrated Systems 2009
Country/TerritoryUnited States
CitySan Diego, CA
Period9/03/0912/03/09

Keywords

  • Adaptive fuzzy control
  • Decentralized control
  • Hysteretic model
  • Nonlinear control

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