Multi-Objective Optimization of LQR Control Quarter Car Suspension System using Genetic Algorithm

被引：13
|
作者：
Nagarkar, M. P. [1 ,2 ]
Patil, G. J. Vikhe [3 ]
机构：
[1] SCSM Coll Engn, Ahmednagar 414005, MS, India
[2] AV Coll Engn, Sangamner, India
[3] AV Coll Engn, Ahmednagar, MS, India
来源：
FME TRANSACTIONS | 2016年 / 44卷 / 02期
关键词：
Genetic Algorithm; Multi-objective optimization; Macpherson strut; Quarter car; LQR;
D O I：
10.5937/fmet1602187N
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In this paper, genetic algorithm (GA) based multi-objective optimization technique is presented to search optimum weighting matrix parameters of linear quadratic regulator (LQR). Macpherson strut suspension system is implemented for study. GA is implemented to minimize vibration dose values (VDV), RMS sprung mass acceleration, sprung mass displacement and suspension working space. Constraints are put on RMS sprung mass acceleration, maximum sprung mass acceleration, tyre deflection, unsprung mass displacement and RMS control force. Passive suspension system and LQR control active suspension system are simulated in time domain. Results are compared using class E road and vehicle speed 80 kmph. For step response, GA based LQR control system is having minimum oscillations with good ride comfort. VDV is reduced by 16.54%, 40.79% and 67.34% for Case I, II and III respectively. Same trend is observed for RMS sprung mass acceleration. Pareto-front gives more flexibility to choose optimum solution as per designer's need.
引用
收藏
页码：187 / 196
页数：10
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