Abstract
In this research, novel genetic algorithm (nGA) is proposed for Bouc-Wen modle parameters esstimation for magnetorheological (MR) fluid dampers. The optimization efficiency is improved by modifying the crossover and mutation steps of a GA. In the crossover stage, the probability of reproducing offspring from the same parent (same mother and father chromosome) is done to be zero, which may happen in the standard GA, and the probability of a chromosome to be selected for mating is based on error rank weighting of the chromosomes. Additional fitness evaluation of chromosomes will take place in between the crossover and mutation steps to save the best chromosome found so far, which is not implemented in the standard genetic algorithm (GA). The model is validated by comparing its simulation output force ( Fsim) with experimentally generated MR damper force ( Fexp). The mean absolute error, standard deviation and number of generations for convergence are taken as a criterias for performance evaluation. With these ctriterias, the proposed novel GA outperform better than the other researches. The accuracy is improved by 46.67% compared to standard GA. The proposed novel GA for Bouc-Wen model parameter identification can be used for any MR damper control system with better accuracy.
Highlights
Magnetorheological (MR) damper is one of the best candidates of semi-active nonlinear vibration damping system that can be applied to vibration damping of civil structures,[1,2] automotive vehicles, railway vehicles and Hyperloop capsule train suspension systems[3,4,5,6] for its worthwhile features including mechanical simplicity, large force capability, low power requirement, rapid response and robustness
The experimental force ðfiexpÞwill be taken from tÀhe eÁxperimental data and simulation force fisim is generated from the Bouc-Wen MR damper model using 4th order Rung-Kutta routine with chromosomes Cvar, j obtained from the proposed novel genetic algorithm (GA) (using equations (2) and (3))
Experimental data, which are extracted from the experiment under different combinations of inputs, are fed to the proposed novel GA, efficient GA proposed on article,[16] normalized Bouc-Wen model proposed on article,[31] and standard GA to find out model parameters
Summary
Magnetorheological (MR) damper is one of the best candidates of semi-active nonlinear vibration damping system that can be applied to vibration damping of civil structures,[1,2] automotive vehicles, railway vehicles and Hyperloop capsule train suspension systems[3,4,5,6] for its worthwhile features including mechanical simplicity, large force capability, low power requirement, rapid response and robustness. In Kwok et al.,[16] a computational efficient genetic algorithm is proposed to identify of Bouc-Wen model parameters of MR damper. In Xiaomin et al.,[34] the authors proposed modified genetic algorithm and a simplified Bouc-Wen model for MR damper They did a sensitivity analysis and concluded that co; ko; fo; andn parameters significantly affect the shape of the hysteresis loop at different input current, so these parameters are considered to be functions of the excitation current, and the other four parameters are taken as a constant. A Bouc-Wen model with novel genetic algorithm parameter identification is proposed for MR damper dynamics analysis. The experimental force ðfiexpÞwill be taken from tÀhe eÁxperimental data and simulation (predicted) force fisim is generated from the Bouc-Wen MR damper model using 4th order Rung-Kutta routine with chromosomes (a set of parameters) Cvar, j obtained from the proposed novel GA (using equations (2) and (3)). The GA will terminate at generation q such that ðq.qminÞLðl ł 0:2maxðeqminÞÞ ð19Þ
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