An Adaptive and Robust Control Strategy for Real-Time Hybrid Simulation

Hong Wei Li, Fang Wang, Yi Qing Ni, You Wu Wang, Zhao Dong Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

A real-time hybrid simulation (RTHS) is a promising technique to investigate a complicated or large-scale structure by dividing it into numerical and physical substructures and conducting cyber-physical tests on it. The control system design of an RTHS is a challenging topic due to the additional feedback between the physical and numerical substructures, and the complexity of the physical control plant. This paper proposes a novel RTHS control strategy by combining the theories of adaptive control and robust control, where a reformed plant which is highly simplified compared to the physical plant can be used to design the control system without compromising the control performance. The adaptation and robustness features of the control system are realized by the bounded-gain forgetting least-squares estimator and the sliding mode controller, respectively. The control strategy is validated by investigating an RTHS benchmark problem of a nonlinear three-story steel frame The proposed control strategy could simplify the control system design and does not require a precise physical plant; thus, it is an efficient and practical option for an RTHS.

Original languageEnglish
Article number6569
JournalSensors
Volume22
Issue number17
DOIs
Publication statusPublished - Sept 2022

Keywords

  • adaptation
  • benchmark
  • bounded-gain forgetting
  • least-squares estimator
  • real-time hybrid simulation
  • robustness
  • sliding mode control

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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