Smart Structures and Systems

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Control strategy for the substructuring testing systems to simulate soil-structure interaction

  • Guo, Jun (The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology) ;
  • Tang, Zhenyun (The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology) ;
  • Chen, Shicai (The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology) ;
  • Li, Zhenbao (The Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology)
  • Received : 2015.10.14
  • Accepted : 2016.08.28
  • Published : 2016.12.25
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Abstract

Real-time substructuring techniques are currently an advanced experimental method for testing large size specimens in the laboratory. In dynamic substructuring, the whole tested system is split into two linked parts, the part of particular interest or nonlinearity, which is tested physically, and the remanding part which is tested numerically. To achieve near-perfect synchronization of the interface response between the physical specimen and the numerical model, a good controller is needed to compensate for transfer system dynamics, nonlinearities, uncertainties and time-varying parameters within the physical substructures. This paper presents the substructuring approach and control performance of the linear and the adaptive controllers for testing the dynamic characteristics of soil-structure-interaction system (SSI). This is difficult to emulate as an entire system in the laboratory because of the size and power supply limitations of the experimental facilities. A modified linear substructuring controller (MLSC) is proposed to replace the linear substructuring controller (LSC).The MLSC doesn't require the accurate mathematical model of the physical structure that is required by the LSC. The effects of parameter identification errors of physical structure and the shaking table on the control performance of the MLSC are analysed. An adaptive controller was designed to compensate for the errors from the simplification of the physical model in the MLSC, and from parameter identification errors. Comparative simulation and experimental tests were then performed to evaluate the performance of the MLSC and the adaptive controller.

Keywords

Acknowledgement

Supported by : Beijing Natural Science Foundation

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