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Performance Examination of Nonlinear Signal-Based Control in Shake Table Experiments with Sliding Structures

Author(s): ORCID
ORCID
ORCID

Medium: journal article
Language(s): English
Published in: Structural Control and Health Monitoring, , v. 2023
Page(s): 1-21
DOI: 10.1155/2023/9526244
Abstract:

This study examines nonlinear signal-based control (NSBC) in shake table experiments with sliding structures, which have an isolation effect during an earthquake. NSBC uses a nonlinear signal obtained from the outputs of a controlled system and its linear model under the same input. Owing to the presence of the linear model, NSBC controllers are described by transfer functions, even for controlling nonlinear systems. NSBC achieved excellent control of the shake table in experiments with a specimen having nonlinear characteristics such as yielding of structural components. A sliding structure placed on a shake table significantly jeopardises its control because the nonlinear severity of sliding is greater than yielding, and its compensation has not yet been fully developed. Therefore, this study introduces NSBC into shake table experiments with sliding structures along with its linear model design to enhance their robustness, utilising the analysis stability to evaluate the design. Numerical simulations with a shake table with a sliding structure with a friction coefficient of 0.22 demonstrate the excellent performance of NSBC in table acceleration control. However, inversion-based control (IBC), a basic compensation approach, shows its ineffectiveness. In actual shake table experiments with a sliding structure with a friction coefficient of 0.2, NSBC with a reasonable linear model achieved excellent table acceleration control with almost 100% accuracy, whereas IBC was ineffective. This study clarifies that NSBC can solve the problem of control degradation caused by a sliding structure placed on the table.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1155/2023/9526244.
  • About this
    data sheet
  • Reference-ID
    10734833
  • Published on:
    03/09/2023
  • Last updated on:
    03/09/2023
 
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