Real-time damping-force tracking control of self-sensing magnetorheological dampers

Zhao Hui Chen, Yiqing Ni

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

All right reserved. In order to enhance the control performance of a self-sensing magnetorheological damper (SMRD), an inverse dynamics-based collocated linear-quadratic-Gaussian (LQG) control strategy (i-LQG) was proposed. Control-oriented forward and inverse dynamic models of the SMRD were developed by employing a Bayesian NARX (nonlinear autoregressive with exogenous inputs) network technique to represent its nonlinear dynamics. The dynamic models were further incorporated into the LQG control loop to compensate for the hysteretic nonlinearity of the SMRD and to implement semi-active damping-force tracking control. Experiments were conducted to compare the real-time force tracking performance when the SMRD was controlled by the i-LQG control and the Heaviside step function-based LQG (H-LQG) control, respectively. Results show that the i-LQG control commands continuously varying voltage to enhance the real-time SMRD damping-force tracking with a 50% reduction of the force tracking error beyond the H-LQG control. The structural damping with the i-LQG control is increased by 11% compared with that with the H-LQG control, which verifies that the proposed i-LQG control is able to realize more efficient semi-active structural control performance.
Original languageEnglish
Pages (from-to)1551-1558
Number of pages8
JournalZhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science)
Volume51
Issue number8
DOIs
Publication statusPublished - 1 Aug 2017

Keywords

  • Bayesian NARX network
  • Dynamic model
  • Force tracking
  • Real-time control
  • Self-sensing magnetorheological damper

ASJC Scopus subject areas

  • Engineering(all)

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