Characterization and modeling of a self-sensing MR damper under harmonic loading

Z. H. Chen, Yiqing Ni, Siu Wing Or

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)


A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.
Original languageEnglish
Pages (from-to)1103-1120
Number of pages18
JournalSmart Structures and Systems
Issue number4
Publication statusPublished - 1 Jan 2015


  • Bayesian regularization
  • Dynamic modeling
  • Hysteresis
  • NARX neural network
  • Piezoelectric force sensor
  • Self-sensing magnetorheological (MR) damper

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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