Optimized Fuzzy Skyhook Control for Semi-Active Vehicle Suspension with New Inverse Model of Magnetorheological Fluid Damper

被引：36

作者：

Ma, Teng ^{[1
]}

Bi, Fengrong ^{[1
]}

Wang, Xu ^{[2
]}

Tian, Congfeng ^{[3
]}

Lin, Jiewei ^{[1
]}

Wang, Jie ^{[1
]}

Pang, Gejun ^{[1
]}

机构：

[1] Tianjin Univ, State Key Lab Engines, Tianjin 300072, Peoples R China

[2] RMIT Univ, Sch Engn, Melbourne, Vic 3000, Australia

[3] Shantui Construct Machinery CO LTD, Jining 272000, Peoples R China

来源：

ENERGIES | 2021年 / 14卷 / 06期

关键词：

magnetorheological fluid damper; inverse model; Elman neural network; grey wolf optimizer; semi-active suspension;

D O I：

10.3390/en14061674

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

To improve the performance of vehicle suspension, this paper proposes a semi-active vehicle suspension with a magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller with grey wolf optimizer (GWO) algorithm base on a new neuro-inverse model of the MRF damper. Because the inverse model of the MRF damper is difficult to establish directly, the Elman neural network was applied. The novelty of this study is the application of the new inverse model for semi-active vibration control and optimization of the semi-active suspension control method. The calculation results showed that the new inverse model can accurately calculate the required control current. The fuzzy skyhook control method optimized by the grey wolf optimizer (GWO) algorithm was established based on the inverse model to control the suspension vibration. The simulation results showed that the optimized fuzzy skyhook control method can simultaneously reduce the amplitude of vertical acceleration, suspension deflection, and tire dynamic load.

引用

页数：21

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