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A new AI-surrogate model for dynamics analysis of a magnetorheological damper in the semi-active seat suspension

Journal Article


Abstract


  • © 2020 The Author(s). Published by IOP Publishing Ltd. This paper aims to develop a surrogate model for dynamics analysis of a magnetorheological damper (MRD) in the semi-active seat suspension system. An improved fruit fly optimization algorithm (IFOA) which enhances the global search capability of the original FOA is proposed to optimize the structure of a back propagation neural network (BPNN) in establishing the surrogate model. An MRD platform was fabricated to generate experimental data to feed the IFOA-BPNN model. Intrinsic patterns about the MRD dynamics behind the datasets have been discovered to establish a reliable MRD surrogate model. The outputs of the surrogate model demonstrate satisfactory dynamics characteristics in consistence with the experimental results. Moreover, the performance of the IFOA-BPNN based surrogate model was compared with that produced by the BPNN based, genetic algorithm-BPNN based, and FOA-BPNN based surrogate models. The comparison result shows better tracking capacity of the proposed method on the hysteresis behaviors of the MRD. As a result, the newly developed surrogate model can be used as the basis for advanced controller design of the semi-active seat suspension system.

Authors


  •   Liu, Xinhua (external author)
  •   Wang, Ningning (external author)
  •   Wang, Kun (external author)
  •   Chen, Shumei (external author)
  •   Sun, Shuai
  •   Li, Zhixiong
  •   Li, Weihua

Publication Date


  • 2020

Citation


  • Liu, X., Wang, N., Wang, K., Chen, S., Sun, S., Li, Z. & Li, W. (2020). A new AI-surrogate model for dynamics analysis of a magnetorheological damper in the semi-active seat suspension. Smart Materials and Structures, 29 (3),

Scopus Eid


  • 2-s2.0-85082241464

Volume


  • 29

Issue


  • 3

Place Of Publication


  • United Kingdom

Abstract


  • © 2020 The Author(s). Published by IOP Publishing Ltd. This paper aims to develop a surrogate model for dynamics analysis of a magnetorheological damper (MRD) in the semi-active seat suspension system. An improved fruit fly optimization algorithm (IFOA) which enhances the global search capability of the original FOA is proposed to optimize the structure of a back propagation neural network (BPNN) in establishing the surrogate model. An MRD platform was fabricated to generate experimental data to feed the IFOA-BPNN model. Intrinsic patterns about the MRD dynamics behind the datasets have been discovered to establish a reliable MRD surrogate model. The outputs of the surrogate model demonstrate satisfactory dynamics characteristics in consistence with the experimental results. Moreover, the performance of the IFOA-BPNN based surrogate model was compared with that produced by the BPNN based, genetic algorithm-BPNN based, and FOA-BPNN based surrogate models. The comparison result shows better tracking capacity of the proposed method on the hysteresis behaviors of the MRD. As a result, the newly developed surrogate model can be used as the basis for advanced controller design of the semi-active seat suspension system.

Authors


  •   Liu, Xinhua (external author)
  •   Wang, Ningning (external author)
  •   Wang, Kun (external author)
  •   Chen, Shumei (external author)
  •   Sun, Shuai
  •   Li, Zhixiong
  •   Li, Weihua

Publication Date


  • 2020

Citation


  • Liu, X., Wang, N., Wang, K., Chen, S., Sun, S., Li, Z. & Li, W. (2020). A new AI-surrogate model for dynamics analysis of a magnetorheological damper in the semi-active seat suspension. Smart Materials and Structures, 29 (3),

Scopus Eid


  • 2-s2.0-85082241464

Volume


  • 29

Issue


  • 3

Place Of Publication


  • United Kingdom