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FME Transactions
2016, vol. 44, iss. 2, pp. 187-196
article language: English
document type: unclassified
published on: 25/06/2016
doi: 10.5937/fmet1602187N
Creative Commons License 4.0
Multi-objective optimization of LQR control quarter car suspension system using genetic algorithm
aSCSM College of Engineering, Ahmednagar (MS), India + AV College of Engineering, Sangamner, India
bAV College of Engineering,Sangamner, Ahmednagar (MS), India



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.


Genetic Algorithm; Multi-objective optimization; Macpherson strut; Quarter car; LQR


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